update trailing char
This commit is contained in:
Lorenzo Volpi
parent
6d51bb730a
commit
f1c6b0c29c
|
|
@ -1,20 +1,20 @@
|
|||
*.code-workspace
|
||||
quavenv/*
|
||||
*.pdf
|
||||
|
||||
__pycache__/*
|
||||
baselines/__pycache__/*
|
||||
baselines/densratio/__pycache__/*
|
||||
quacc/__pycache__/*
|
||||
quacc/evaluation/__pycache__/*
|
||||
quacc/method/__pycache__/*
|
||||
tests/__pycache__/*
|
||||
|
||||
*.coverage
|
||||
.coverage
|
||||
|
||||
scp_sync.py
|
||||
|
||||
out/*
|
||||
output/*
|
||||
*.code-workspace
|
||||
quavenv/*
|
||||
*.pdf
|
||||
|
||||
__pycache__/*
|
||||
baselines/__pycache__/*
|
||||
baselines/densratio/__pycache__/*
|
||||
quacc/__pycache__/*
|
||||
quacc/evaluation/__pycache__/*
|
||||
quacc/method/__pycache__/*
|
||||
tests/__pycache__/*
|
||||
|
||||
*.coverage
|
||||
.coverage
|
||||
|
||||
scp_sync.py
|
||||
|
||||
out/*
|
||||
output/*
|
||||
!output/main/
|
||||
|
|
@ -1,25 +1,25 @@
|
|||
{
|
||||
// Use IntelliSense to learn about possible attributes.
|
||||
// Hover to view descriptions of existing attributes.
|
||||
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
|
||||
"version": "0.2.0",
|
||||
"configurations": [
|
||||
|
||||
{
|
||||
"name": "main",
|
||||
"type": "python",
|
||||
"request": "launch",
|
||||
"program": "C:\\Users\\Lorenzo Volpi\\source\\tesi\\quacc\\main.py",
|
||||
"console": "integratedTerminal",
|
||||
"justMyCode": true
|
||||
},
|
||||
{
|
||||
"name": "main_test",
|
||||
"type": "python",
|
||||
"request": "launch",
|
||||
"program": "C:\\Users\\Lorenzo Volpi\\source\\tesi\\quacc\\main_test.py",
|
||||
"console": "integratedTerminal",
|
||||
"justMyCode": false
|
||||
},
|
||||
]
|
||||
{
|
||||
// Use IntelliSense to learn about possible attributes.
|
||||
// Hover to view descriptions of existing attributes.
|
||||
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
|
||||
"version": "0.2.0",
|
||||
"configurations": [
|
||||
|
||||
{
|
||||
"name": "main",
|
||||
"type": "python",
|
||||
"request": "launch",
|
||||
"program": "C:\\Users\\Lorenzo Volpi\\source\\tesi\\quacc\\main.py",
|
||||
"console": "integratedTerminal",
|
||||
"justMyCode": true
|
||||
},
|
||||
{
|
||||
"name": "main_test",
|
||||
"type": "python",
|
||||
"request": "launch",
|
||||
"program": "C:\\Users\\Lorenzo Volpi\\source\\tesi\\quacc\\main_test.py",
|
||||
"console": "integratedTerminal",
|
||||
"justMyCode": false
|
||||
},
|
||||
]
|
||||
}
|
||||
|
|
@ -1,54 +1,54 @@
|
|||
{
|
||||
"todo": [
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:33:36.069Z",
|
||||
"id": "2",
|
||||
"references": [],
|
||||
"title": "Creare plot avg con training prevalence sull'asse x e media rispetto a test prevalence"
|
||||
},
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:32:37.610Z",
|
||||
"id": "1",
|
||||
"references": [],
|
||||
"title": "Testare su imdb"
|
||||
}
|
||||
],
|
||||
"in-progress": [
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:34:23.217Z",
|
||||
"id": "3",
|
||||
"references": [],
|
||||
"title": "Relaizzare grid search per task specifico partedno da GridSearchQ"
|
||||
},
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:34:46.226Z",
|
||||
"id": "4",
|
||||
"references": [],
|
||||
"title": "Aggingere estimator basati su PACC (quantificatore)"
|
||||
}
|
||||
],
|
||||
"testing": [],
|
||||
"done": [
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:35:12.683Z",
|
||||
"id": "5",
|
||||
"references": [],
|
||||
"title": "Rework rappresentazione dati di report"
|
||||
}
|
||||
]
|
||||
{
|
||||
"todo": [
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:33:36.069Z",
|
||||
"id": "2",
|
||||
"references": [],
|
||||
"title": "Creare plot avg con training prevalence sull'asse x e media rispetto a test prevalence"
|
||||
},
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:32:37.610Z",
|
||||
"id": "1",
|
||||
"references": [],
|
||||
"title": "Testare su imdb"
|
||||
}
|
||||
],
|
||||
"in-progress": [
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:34:23.217Z",
|
||||
"id": "3",
|
||||
"references": [],
|
||||
"title": "Relaizzare grid search per task specifico partedno da GridSearchQ"
|
||||
},
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:34:46.226Z",
|
||||
"id": "4",
|
||||
"references": [],
|
||||
"title": "Aggingere estimator basati su PACC (quantificatore)"
|
||||
}
|
||||
],
|
||||
"testing": [],
|
||||
"done": [
|
||||
{
|
||||
"assignedTo": {
|
||||
"name": "Lorenzo Volpi"
|
||||
},
|
||||
"creation_time": "2023-10-28T14:35:12.683Z",
|
||||
"id": "5",
|
||||
"references": [],
|
||||
"title": "Rework rappresentazione dati di report"
|
||||
}
|
||||
]
|
||||
}
|
||||
284
TODO.html
284
TODO.html
|
|
@ -1,143 +1,143 @@
|
|||
<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<title></title>
|
||||
<style>
|
||||
/* From extension vscode.github */
|
||||
/*---------------------------------------------------------------------------------------------
|
||||
* Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
* Licensed under the MIT License. See License.txt in the project root for license information.
|
||||
*--------------------------------------------------------------------------------------------*/
|
||||
|
||||
.vscode-dark img[src$=\#gh-light-mode-only],
|
||||
.vscode-light img[src$=\#gh-dark-mode-only] {
|
||||
display: none;
|
||||
}
|
||||
|
||||
</style>
|
||||
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/Microsoft/vscode/extensions/markdown-language-features/media/markdown.css">
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/Microsoft/vscode/extensions/markdown-language-features/media/highlight.css">
|
||||
<style>
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, 'Segoe WPC', 'Segoe UI', system-ui, 'Ubuntu', 'Droid Sans', sans-serif;
|
||||
font-size: 14px;
|
||||
line-height: 1.6;
|
||||
}
|
||||
</style>
|
||||
<style>
|
||||
.task-list-item {
|
||||
list-style-type: none;
|
||||
}
|
||||
|
||||
.task-list-item-checkbox {
|
||||
margin-left: -20px;
|
||||
vertical-align: middle;
|
||||
pointer-events: none;
|
||||
}
|
||||
</style>
|
||||
|
||||
</head>
|
||||
<body class="vscode-body vscode-light">
|
||||
<ul class="contains-task-list">
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere media tabelle</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> plot; 3 tipi (appunti + email + garg)</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> sistemare kfcv baseline</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere metodo con CC oltre SLD</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> prendere classe più popolosa di rcv1, togliere negativi fino a raggiungere 50/50; poi fare subsampling con 9 training prvalences (da 0.1-0.9 a 0.9-0.1)</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> variare parametro recalibration in SLD</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> fix grafico diagonal</p>
|
||||
<ul>
|
||||
<li>seaborn example gallery</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> varianti recalib: bcts, SLD (provare exact_train_prev=False)</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> vedere cosa usa garg di validation size</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> per model selection testare il parametro c del classificatore, si esplora in np.logscale(-3,3, 7) oppure np.logscale(-4, 4, 9), parametro class_weight si esplora in None oppure "balanced"; va usato qp.model_selection.GridSearchQ in funzione di mae come errore, UPP come protocollo</p>
|
||||
<ul>
|
||||
<li>qp.train_test_split per avere v_train e v_val</li>
|
||||
<li>GridSearchQ(
|
||||
model: BaseQuantifier,
|
||||
param_grid: {
|
||||
'classifier__C': np.logspace(-3,3,7),
|
||||
'classifier__class_weight': [None, 'balanced'],
|
||||
'recalib': [None, 'bcts']
|
||||
},
|
||||
protocol: UPP(V_val, repeats=1000),
|
||||
error = qp.error.mae,
|
||||
refit=True,
|
||||
timeout=-1,
|
||||
n_jobs=-2,
|
||||
verbose=True).fit(V_tr)</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> plot collettivo, con sulla x lo shift e prenda in considerazione tutti i training set, facendo la media sui 9 casi (ogni line è un metodo), risultati non ottimizzati e ottimizzati</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> salvare il best score ottenuto da ogni applicazione di GridSearchQ</p>
|
||||
<ul>
|
||||
<li>nel caso di bin fare media dei due best score</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> import baselines</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox"type="checkbox"> importare mandoline</p>
|
||||
<ul>
|
||||
<li>mandoline può essere importato, ma richiedere uno slicing delle features a priori che devere essere realizzato ad hoc</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox"type="checkbox"> sistemare vecchie iw baselines</p>
|
||||
<ul>
|
||||
<li>non possono essere fixate perché dipendono da numpy</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> plot avg con train prevalence sull'asse x e media su test prevalecne</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> realizzare grid search per task specifico partendo da GridSearchQ</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> provare PACC come quantificatore</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere etichette in shift plot</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> sistemare exact_train quapy</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> testare anche su imbd</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox"type="checkbox"> rivedere nuove baselines</p>
|
||||
</li>
|
||||
</ul>
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<title></title>
|
||||
<style>
|
||||
/* From extension vscode.github */
|
||||
/*---------------------------------------------------------------------------------------------
|
||||
* Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
* Licensed under the MIT License. See License.txt in the project root for license information.
|
||||
*--------------------------------------------------------------------------------------------*/
|
||||
|
||||
.vscode-dark img[src$=\#gh-light-mode-only],
|
||||
.vscode-light img[src$=\#gh-dark-mode-only] {
|
||||
display: none;
|
||||
}
|
||||
|
||||
</style>
|
||||
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/Microsoft/vscode/extensions/markdown-language-features/media/markdown.css">
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/Microsoft/vscode/extensions/markdown-language-features/media/highlight.css">
|
||||
<style>
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, 'Segoe WPC', 'Segoe UI', system-ui, 'Ubuntu', 'Droid Sans', sans-serif;
|
||||
font-size: 14px;
|
||||
line-height: 1.6;
|
||||
}
|
||||
</style>
|
||||
<style>
|
||||
.task-list-item {
|
||||
list-style-type: none;
|
||||
}
|
||||
|
||||
.task-list-item-checkbox {
|
||||
margin-left: -20px;
|
||||
vertical-align: middle;
|
||||
pointer-events: none;
|
||||
}
|
||||
</style>
|
||||
|
||||
</head>
|
||||
<body class="vscode-body vscode-light">
|
||||
<ul class="contains-task-list">
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere media tabelle</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> plot; 3 tipi (appunti + email + garg)</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> sistemare kfcv baseline</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere metodo con CC oltre SLD</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> prendere classe più popolosa di rcv1, togliere negativi fino a raggiungere 50/50; poi fare subsampling con 9 training prvalences (da 0.1-0.9 a 0.9-0.1)</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> variare parametro recalibration in SLD</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> fix grafico diagonal</p>
|
||||
<ul>
|
||||
<li>seaborn example gallery</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> varianti recalib: bcts, SLD (provare exact_train_prev=False)</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> vedere cosa usa garg di validation size</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> per model selection testare il parametro c del classificatore, si esplora in np.logscale(-3,3, 7) oppure np.logscale(-4, 4, 9), parametro class_weight si esplora in None oppure "balanced"; va usato qp.model_selection.GridSearchQ in funzione di mae come errore, UPP come protocollo</p>
|
||||
<ul>
|
||||
<li>qp.train_test_split per avere v_train e v_val</li>
|
||||
<li>GridSearchQ(
|
||||
model: BaseQuantifier,
|
||||
param_grid: {
|
||||
'classifier__C': np.logspace(-3,3,7),
|
||||
'classifier__class_weight': [None, 'balanced'],
|
||||
'recalib': [None, 'bcts']
|
||||
},
|
||||
protocol: UPP(V_val, repeats=1000),
|
||||
error = qp.error.mae,
|
||||
refit=True,
|
||||
timeout=-1,
|
||||
n_jobs=-2,
|
||||
verbose=True).fit(V_tr)</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> plot collettivo, con sulla x lo shift e prenda in considerazione tutti i training set, facendo la media sui 9 casi (ogni line è un metodo), risultati non ottimizzati e ottimizzati</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> salvare il best score ottenuto da ogni applicazione di GridSearchQ</p>
|
||||
<ul>
|
||||
<li>nel caso di bin fare media dei due best score</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> import baselines</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox"type="checkbox"> importare mandoline</p>
|
||||
<ul>
|
||||
<li>mandoline può essere importato, ma richiedere uno slicing delle features a priori che devere essere realizzato ad hoc</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox"type="checkbox"> sistemare vecchie iw baselines</p>
|
||||
<ul>
|
||||
<li>non possono essere fixate perché dipendono da numpy</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> plot avg con train prevalence sull'asse x e media su test prevalecne</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> realizzare grid search per task specifico partendo da GridSearchQ</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> provare PACC come quantificatore</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere etichette in shift plot</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> sistemare exact_train quapy</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox" checked=""type="checkbox"> testare anche su imbd</p>
|
||||
</li>
|
||||
<li class="task-list-item enabled">
|
||||
<p><input class="task-list-item-checkbox"type="checkbox"> rivedere nuove baselines</p>
|
||||
</li>
|
||||
</ul>
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
86
TODO.md
86
TODO.md
|
|
@ -1,44 +1,44 @@
|
|||
- [x] aggiungere media tabelle
|
||||
- [x] plot; 3 tipi (appunti + email + garg)
|
||||
- [x] sistemare kfcv baseline
|
||||
- [x] aggiungere metodo con CC oltre SLD
|
||||
- [x] prendere classe più popolosa di rcv1, togliere negativi fino a raggiungere 50/50; poi fare subsampling con 9 training prvalences (da 0.1-0.9 a 0.9-0.1)
|
||||
- [x] variare parametro recalibration in SLD
|
||||
|
||||
|
||||
- [x] fix grafico diagonal
|
||||
- seaborn example gallery
|
||||
- [x] varianti recalib: bcts, SLD (provare exact_train_prev=False)
|
||||
- [x] vedere cosa usa garg di validation size
|
||||
- [x] per model selection testare il parametro c del classificatore, si esplora in np.logscale(-3,3, 7) oppure np.logscale(-4, 4, 9), parametro class_weight si esplora in None oppure "balanced"; va usato qp.model_selection.GridSearchQ in funzione di mae come errore, UPP come protocollo
|
||||
- qp.train_test_split per avere v_train e v_val
|
||||
- GridSearchQ(
|
||||
model: BaseQuantifier,
|
||||
param_grid: {
|
||||
'classifier__C': np.logspace(-3,3,7),
|
||||
'classifier__class_weight': [None, 'balanced'],
|
||||
'recalib': [None, 'bcts']
|
||||
},
|
||||
protocol: UPP(V_val, repeats=1000),
|
||||
error = qp.error.mae,
|
||||
refit=True,
|
||||
timeout=-1,
|
||||
n_jobs=-2,
|
||||
verbose=True).fit(V_tr)
|
||||
- [x] plot collettivo, con sulla x lo shift e prenda in considerazione tutti i training set, facendo la media sui 9 casi (ogni line è un metodo), risultati non ottimizzati e ottimizzati
|
||||
- [x] salvare il best score ottenuto da ogni applicazione di GridSearchQ
|
||||
- nel caso di bin fare media dei due best score
|
||||
- [x] import baselines
|
||||
|
||||
- [ ] importare mandoline
|
||||
- mandoline può essere importato, ma richiedere uno slicing delle features a priori che devere essere realizzato ad hoc
|
||||
- [ ] sistemare vecchie iw baselines
|
||||
- non possono essere fixate perché dipendono da numpy
|
||||
- [x] plot avg con train prevalence sull'asse x e media su test prevalecne
|
||||
- [x] realizzare grid search per task specifico partendo da GridSearchQ
|
||||
- [x] provare PACC come quantificatore
|
||||
- [x] aggiungere etichette in shift plot
|
||||
- [x] sistemare exact_train quapy
|
||||
- [x] testare anche su imbd
|
||||
|
||||
- [x] aggiungere media tabelle
|
||||
- [x] plot; 3 tipi (appunti + email + garg)
|
||||
- [x] sistemare kfcv baseline
|
||||
- [x] aggiungere metodo con CC oltre SLD
|
||||
- [x] prendere classe più popolosa di rcv1, togliere negativi fino a raggiungere 50/50; poi fare subsampling con 9 training prvalences (da 0.1-0.9 a 0.9-0.1)
|
||||
- [x] variare parametro recalibration in SLD
|
||||
|
||||
|
||||
- [x] fix grafico diagonal
|
||||
- seaborn example gallery
|
||||
- [x] varianti recalib: bcts, SLD (provare exact_train_prev=False)
|
||||
- [x] vedere cosa usa garg di validation size
|
||||
- [x] per model selection testare il parametro c del classificatore, si esplora in np.logscale(-3,3, 7) oppure np.logscale(-4, 4, 9), parametro class_weight si esplora in None oppure "balanced"; va usato qp.model_selection.GridSearchQ in funzione di mae come errore, UPP come protocollo
|
||||
- qp.train_test_split per avere v_train e v_val
|
||||
- GridSearchQ(
|
||||
model: BaseQuantifier,
|
||||
param_grid: {
|
||||
'classifier__C': np.logspace(-3,3,7),
|
||||
'classifier__class_weight': [None, 'balanced'],
|
||||
'recalib': [None, 'bcts']
|
||||
},
|
||||
protocol: UPP(V_val, repeats=1000),
|
||||
error = qp.error.mae,
|
||||
refit=True,
|
||||
timeout=-1,
|
||||
n_jobs=-2,
|
||||
verbose=True).fit(V_tr)
|
||||
- [x] plot collettivo, con sulla x lo shift e prenda in considerazione tutti i training set, facendo la media sui 9 casi (ogni line è un metodo), risultati non ottimizzati e ottimizzati
|
||||
- [x] salvare il best score ottenuto da ogni applicazione di GridSearchQ
|
||||
- nel caso di bin fare media dei due best score
|
||||
- [x] import baselines
|
||||
|
||||
- [ ] importare mandoline
|
||||
- mandoline può essere importato, ma richiedere uno slicing delle features a priori che devere essere realizzato ad hoc
|
||||
- [ ] sistemare vecchie iw baselines
|
||||
- non possono essere fixate perché dipendono da numpy
|
||||
- [x] plot avg con train prevalence sull'asse x e media su test prevalecne
|
||||
- [x] realizzare grid search per task specifico partendo da GridSearchQ
|
||||
- [x] provare PACC come quantificatore
|
||||
- [x] aggiungere etichette in shift plot
|
||||
- [x] sistemare exact_train quapy
|
||||
- [x] testare anche su imbd
|
||||
|
||||
- [ ] rivedere nuove baselines
|
||||
|
|
@ -1,44 +1,44 @@
|
|||
import numpy as np
|
||||
from sklearn.metrics import f1_score
|
||||
|
||||
|
||||
def get_entropy(probs):
|
||||
return np.sum(np.multiply(probs, np.log(probs + 1e-20)), axis=1)
|
||||
|
||||
|
||||
def get_max_conf(probs):
|
||||
return np.max(probs, axis=-1)
|
||||
|
||||
|
||||
def find_ATC_threshold(scores, labels):
|
||||
sorted_idx = np.argsort(scores)
|
||||
|
||||
sorted_scores = scores[sorted_idx]
|
||||
sorted_labels = labels[sorted_idx]
|
||||
|
||||
fp = np.sum(labels == 0)
|
||||
fn = 0.0
|
||||
|
||||
min_fp_fn = np.abs(fp - fn)
|
||||
thres = 0.0
|
||||
for i in range(len(labels)):
|
||||
if sorted_labels[i] == 0:
|
||||
fp -= 1
|
||||
else:
|
||||
fn += 1
|
||||
|
||||
if np.abs(fp - fn) < min_fp_fn:
|
||||
min_fp_fn = np.abs(fp - fn)
|
||||
thres = sorted_scores[i]
|
||||
|
||||
return min_fp_fn, thres
|
||||
|
||||
|
||||
def get_ATC_acc(thres, scores):
|
||||
return np.mean(scores >= thres)
|
||||
|
||||
|
||||
def get_ATC_f1(thres, scores, probs):
|
||||
preds = np.argmax(probs, axis=-1)
|
||||
estim_y = np.abs(1 - (scores >= thres) ^ preds)
|
||||
return f1_score(estim_y, preds)
|
||||
import numpy as np
|
||||
from sklearn.metrics import f1_score
|
||||
|
||||
|
||||
def get_entropy(probs):
|
||||
return np.sum(np.multiply(probs, np.log(probs + 1e-20)), axis=1)
|
||||
|
||||
|
||||
def get_max_conf(probs):
|
||||
return np.max(probs, axis=-1)
|
||||
|
||||
|
||||
def find_ATC_threshold(scores, labels):
|
||||
sorted_idx = np.argsort(scores)
|
||||
|
||||
sorted_scores = scores[sorted_idx]
|
||||
sorted_labels = labels[sorted_idx]
|
||||
|
||||
fp = np.sum(labels == 0)
|
||||
fn = 0.0
|
||||
|
||||
min_fp_fn = np.abs(fp - fn)
|
||||
thres = 0.0
|
||||
for i in range(len(labels)):
|
||||
if sorted_labels[i] == 0:
|
||||
fp -= 1
|
||||
else:
|
||||
fn += 1
|
||||
|
||||
if np.abs(fp - fn) < min_fp_fn:
|
||||
min_fp_fn = np.abs(fp - fn)
|
||||
thres = sorted_scores[i]
|
||||
|
||||
return min_fp_fn, thres
|
||||
|
||||
|
||||
def get_ATC_acc(thres, scores):
|
||||
return np.mean(scores >= thres)
|
||||
|
||||
|
||||
def get_ATC_f1(thres, scores, probs):
|
||||
preds = np.argmax(probs, axis=-1)
|
||||
estim_y = np.abs(1 - (scores >= thres) ^ preds)
|
||||
return f1_score(estim_y, preds)
|
||||
|
|
|
|||
|
|
@ -1,277 +1,277 @@
|
|||
"""
|
||||
Relative Unconstrained Least-Squares Fitting (RuLSIF): A Python Implementation
|
||||
References:
|
||||
'Change-point detection in time-series data by relative density-ratio estimation'
|
||||
Song Liu, Makoto Yamada, Nigel Collier and Masashi Sugiyama,
|
||||
Neural Networks 43 (2013) 72-83.
|
||||
|
||||
'A Least-squares Approach to Direct Importance Estimation'
|
||||
Takafumi Kanamori, Shohei Hido, and Masashi Sugiyama,
|
||||
Journal of Machine Learning Research 10 (2009) 1391-1445.
|
||||
"""
|
||||
|
||||
from warnings import warn
|
||||
|
||||
from numpy import (
|
||||
array,
|
||||
asarray,
|
||||
asmatrix,
|
||||
diag,
|
||||
diagflat,
|
||||
empty,
|
||||
exp,
|
||||
inf,
|
||||
log,
|
||||
matrix,
|
||||
multiply,
|
||||
ones,
|
||||
power,
|
||||
sum,
|
||||
)
|
||||
from numpy.linalg import solve
|
||||
from numpy.random import randint
|
||||
|
||||
from .density_ratio import DensityRatio, KernelInfo
|
||||
from .helpers import guvectorize_compute, np_float, to_ndarray
|
||||
|
||||
|
||||
def RuLSIF(x, y, alpha, sigma_range, lambda_range, kernel_num=100, verbose=True):
|
||||
"""
|
||||
Estimation of the alpha-Relative Density Ratio p(x)/p_alpha(x) by RuLSIF
|
||||
(Relative Unconstrained Least-Square Importance Fitting)
|
||||
|
||||
p_alpha(x) = alpha * p(x) + (1 - alpha) * q(x)
|
||||
|
||||
Arguments:
|
||||
x (numpy.matrix): Sample from p(x).
|
||||
y (numpy.matrix): Sample from q(x).
|
||||
alpha (float): Mixture parameter.
|
||||
sigma_range (list<float>): Search range of Gaussian kernel bandwidth.
|
||||
lambda_range (list<float>): Search range of regularization parameter.
|
||||
kernel_num (int): Number of kernels. (Default 100)
|
||||
verbose (bool): Indicator to print messages (Default True)
|
||||
|
||||
Returns:
|
||||
densratio.DensityRatio object which has `compute_density_ratio()`.
|
||||
"""
|
||||
|
||||
# Number of samples.
|
||||
nx = x.shape[0]
|
||||
ny = y.shape[0]
|
||||
|
||||
# Number of kernel functions.
|
||||
kernel_num = min(kernel_num, nx)
|
||||
|
||||
# Randomly take a subset of x, to identify centers for the kernels.
|
||||
centers = x[randint(nx, size=kernel_num)]
|
||||
|
||||
if verbose:
|
||||
print("RuLSIF starting...")
|
||||
|
||||
if len(sigma_range) == 1 and len(lambda_range) == 1:
|
||||
sigma = sigma_range[0]
|
||||
lambda_ = lambda_range[0]
|
||||
else:
|
||||
if verbose:
|
||||
print("Searching for the optimal sigma and lambda...")
|
||||
|
||||
# Grid-search cross-validation for optimal kernel and regularization parameters.
|
||||
opt_params = search_sigma_and_lambda(
|
||||
x, y, alpha, centers, sigma_range, lambda_range, verbose
|
||||
)
|
||||
sigma = opt_params["sigma"]
|
||||
lambda_ = opt_params["lambda"]
|
||||
|
||||
if verbose:
|
||||
print(
|
||||
"Found optimal sigma = {:.3f}, lambda = {:.3f}.".format(sigma, lambda_)
|
||||
)
|
||||
|
||||
if verbose:
|
||||
print("Optimizing theta...")
|
||||
|
||||
phi_x = compute_kernel_Gaussian(x, centers, sigma)
|
||||
phi_y = compute_kernel_Gaussian(y, centers, sigma)
|
||||
H = alpha * (phi_x.T.dot(phi_x) / nx) + (1 - alpha) * (phi_y.T.dot(phi_y) / ny)
|
||||
h = phi_x.mean(axis=0).T
|
||||
theta = asarray(solve(H + diag(array(lambda_).repeat(kernel_num)), h)).ravel()
|
||||
|
||||
# No negative coefficients.
|
||||
theta[theta < 0] = 0
|
||||
|
||||
# Compute the alpha-relative density ratio, at the given coordinates.
|
||||
def alpha_density_ratio(coordinates):
|
||||
# Evaluate the kernel at these coordinates, and take the dot-product with the weights.
|
||||
coordinates = to_ndarray(coordinates)
|
||||
phi_x = compute_kernel_Gaussian(coordinates, centers, sigma)
|
||||
alpha_density_ratio = phi_x @ theta
|
||||
|
||||
return alpha_density_ratio
|
||||
|
||||
# Compute the approximate alpha-relative PE-divergence, given samples x and y from the respective distributions.
|
||||
def alpha_PE_divergence(x, y):
|
||||
# This is Y, in Reference 1.
|
||||
x = to_ndarray(x)
|
||||
|
||||
# Obtain alpha-relative density ratio at these points.
|
||||
g_x = alpha_density_ratio(x)
|
||||
|
||||
# This is Y', in Reference 1.
|
||||
y = to_ndarray(y)
|
||||
|
||||
# Obtain alpha-relative density ratio at these points.
|
||||
g_y = alpha_density_ratio(y)
|
||||
|
||||
# Compute the alpha-relative PE-divergence as given in Reference 1.
|
||||
n = x.shape[0]
|
||||
divergence = (
|
||||
-alpha * (g_x @ g_x) / 2 - (1 - alpha) * (g_y @ g_y) / 2 + g_x.sum(axis=0)
|
||||
) / n - 1.0 / 2
|
||||
return divergence
|
||||
|
||||
# Compute the approximate alpha-relative KL-divergence, given samples x and y from the respective distributions.
|
||||
def alpha_KL_divergence(x, y):
|
||||
# This is Y, in Reference 1.
|
||||
x = to_ndarray(x)
|
||||
|
||||
# Obtain alpha-relative density ratio at these points.
|
||||
g_x = alpha_density_ratio(x)
|
||||
|
||||
# Compute the alpha-relative KL-divergence.
|
||||
n = x.shape[0]
|
||||
divergence = log(g_x).sum(axis=0) / n
|
||||
return divergence
|
||||
|
||||
alpha_PE = alpha_PE_divergence(x, y)
|
||||
alpha_KL = alpha_KL_divergence(x, y)
|
||||
|
||||
if verbose:
|
||||
print("Approximate alpha-relative PE-divergence = {:03.2f}".format(alpha_PE))
|
||||
print("Approximate alpha-relative KL-divergence = {:03.2f}".format(alpha_KL))
|
||||
|
||||
kernel_info = KernelInfo(
|
||||
kernel_type="Gaussian", kernel_num=kernel_num, sigma=sigma, centers=centers
|
||||
)
|
||||
result = DensityRatio(
|
||||
method="RuLSIF",
|
||||
alpha=alpha,
|
||||
theta=theta,
|
||||
lambda_=lambda_,
|
||||
alpha_PE=alpha_PE,
|
||||
alpha_KL=alpha_KL,
|
||||
kernel_info=kernel_info,
|
||||
compute_density_ratio=alpha_density_ratio,
|
||||
)
|
||||
|
||||
if verbose:
|
||||
print("RuLSIF completed.")
|
||||
|
||||
return result
|
||||
|
||||
|
||||
# Grid-search cross-validation for the optimal parameters sigma and lambda by leave-one-out cross-validation. See Reference 2.
|
||||
def search_sigma_and_lambda(x, y, alpha, centers, sigma_range, lambda_range, verbose):
|
||||
nx = x.shape[0]
|
||||
ny = y.shape[0]
|
||||
n_min = min(nx, ny)
|
||||
kernel_num = centers.shape[0]
|
||||
|
||||
score_new = inf
|
||||
sigma_new = 0
|
||||
lambda_new = 0
|
||||
|
||||
for sigma in sigma_range:
|
||||
phi_x = compute_kernel_Gaussian(x, centers, sigma) # (nx, kernel_num)
|
||||
phi_y = compute_kernel_Gaussian(y, centers, sigma) # (ny, kernel_num)
|
||||
H = alpha * (phi_x.T @ phi_x / nx) + (1 - alpha) * (
|
||||
phi_y.T @ phi_y / ny
|
||||
) # (kernel_num, kernel_num)
|
||||
h = phi_x.mean(axis=0).reshape(-1, 1) # (kernel_num, 1)
|
||||
phi_x = phi_x[:n_min].T # (kernel_num, n_min)
|
||||
phi_y = phi_y[:n_min].T # (kernel_num, n_min)
|
||||
|
||||
for lambda_ in lambda_range:
|
||||
B = H + diag(
|
||||
array(lambda_ * (ny - 1) / ny).repeat(kernel_num)
|
||||
) # (kernel_num, kernel_num)
|
||||
B_inv_X = solve(B, phi_y) # (kernel_num, n_min)
|
||||
X_B_inv_X = multiply(phi_y, B_inv_X) # (kernel_num, n_min)
|
||||
denom = ny * ones(n_min) - ones(kernel_num) @ X_B_inv_X # (n_min, )
|
||||
B0 = solve(B, h @ ones((1, n_min))) + B_inv_X @ diagflat(
|
||||
h.T @ B_inv_X / denom
|
||||
) # (kernel_num, n_min)
|
||||
B1 = solve(B, phi_x) + B_inv_X @ diagflat(
|
||||
ones(kernel_num) @ multiply(phi_x, B_inv_X)
|
||||
) # (kernel_num, n_min)
|
||||
B2 = (ny - 1) * (nx * B0 - B1) / (ny * (nx - 1)) # (kernel_num, n_min)
|
||||
B2[B2 < 0] = 0
|
||||
r_y = multiply(phi_y, B2).sum(axis=0).T # (n_min, )
|
||||
r_x = multiply(phi_x, B2).sum(axis=0).T # (n_min, )
|
||||
|
||||
# Squared loss of RuLSIF, without regularization term.
|
||||
# Directly related to the negative of the PE-divergence.
|
||||
score = (r_y @ r_y / 2 - r_x.sum(axis=0)) / n_min
|
||||
|
||||
if verbose:
|
||||
print(
|
||||
"sigma = %.5f, lambda = %.5f, score = %.5f"
|
||||
% (sigma, lambda_, score)
|
||||
)
|
||||
|
||||
if score < score_new:
|
||||
score_new = score
|
||||
sigma_new = sigma
|
||||
lambda_new = lambda_
|
||||
|
||||
return {"sigma": sigma_new, "lambda": lambda_new}
|
||||
|
||||
|
||||
def _compute_kernel_Gaussian(x_list, y_row, neg_gamma, res) -> None:
|
||||
sq_norm = sum(power(x_list - y_row, 2), 1)
|
||||
multiply(neg_gamma, sq_norm, res)
|
||||
exp(res, res)
|
||||
|
||||
|
||||
def _target_numpy_wrapper(x_list, y_list, neg_gamma):
|
||||
res = empty((y_list.shape[0], x_list.shape[0]), np_float)
|
||||
if isinstance(x_list, matrix) or isinstance(y_list, matrix):
|
||||
res = asmatrix(res)
|
||||
|
||||
for j, y_row in enumerate(y_list):
|
||||
# `.T` aligns shapes for matrices, does nothing for 1D ndarray.
|
||||
_compute_kernel_Gaussian(x_list, y_row, neg_gamma, res[j].T)
|
||||
|
||||
return res
|
||||
|
||||
|
||||
_compute_functions = {"numpy": _target_numpy_wrapper}
|
||||
if guvectorize_compute:
|
||||
_compute_functions.update(
|
||||
{
|
||||
key: guvectorize_compute(key)(_compute_kernel_Gaussian)
|
||||
for key in ("cpu", "parallel")
|
||||
}
|
||||
)
|
||||
|
||||
_compute_function = _compute_functions[
|
||||
"cpu" if "cpu" in _compute_functions else "numpy"
|
||||
]
|
||||
|
||||
|
||||
# Returns a 2D numpy matrix of kernel evaluated at the gridpoints with coordinates from x_list and y_list.
|
||||
def compute_kernel_Gaussian(x_list, y_list, sigma):
|
||||
return _compute_function(x_list, y_list, -0.5 * sigma**-2).T
|
||||
|
||||
|
||||
def set_compute_kernel_target(target: str) -> None:
|
||||
global _compute_function
|
||||
if target not in ("numpy", "cpu", "parallel"):
|
||||
raise ValueError(
|
||||
"'target' must be one of the following: 'numpy', 'cpu', or 'parallel'."
|
||||
)
|
||||
|
||||
if target not in _compute_functions:
|
||||
warn("'numba' not available; defaulting to 'numpy'.", ImportWarning)
|
||||
target = "numpy"
|
||||
|
||||
_compute_function = _compute_functions[target]
|
||||
"""
|
||||
Relative Unconstrained Least-Squares Fitting (RuLSIF): A Python Implementation
|
||||
References:
|
||||
'Change-point detection in time-series data by relative density-ratio estimation'
|
||||
Song Liu, Makoto Yamada, Nigel Collier and Masashi Sugiyama,
|
||||
Neural Networks 43 (2013) 72-83.
|
||||
|
||||
'A Least-squares Approach to Direct Importance Estimation'
|
||||
Takafumi Kanamori, Shohei Hido, and Masashi Sugiyama,
|
||||
Journal of Machine Learning Research 10 (2009) 1391-1445.
|
||||
"""
|
||||
|
||||
from warnings import warn
|
||||
|
||||
from numpy import (
|
||||
array,
|
||||
asarray,
|
||||
asmatrix,
|
||||
diag,
|
||||
diagflat,
|
||||
empty,
|
||||
exp,
|
||||
inf,
|
||||
log,
|
||||
matrix,
|
||||
multiply,
|
||||
ones,
|
||||
power,
|
||||
sum,
|
||||
)
|
||||
from numpy.linalg import solve
|
||||
from numpy.random import randint
|
||||
|
||||
from .density_ratio import DensityRatio, KernelInfo
|
||||
from .helpers import guvectorize_compute, np_float, to_ndarray
|
||||
|
||||
|
||||
def RuLSIF(x, y, alpha, sigma_range, lambda_range, kernel_num=100, verbose=True):
|
||||
"""
|
||||
Estimation of the alpha-Relative Density Ratio p(x)/p_alpha(x) by RuLSIF
|
||||
(Relative Unconstrained Least-Square Importance Fitting)
|
||||
|
||||
p_alpha(x) = alpha * p(x) + (1 - alpha) * q(x)
|
||||
|
||||
Arguments:
|
||||
x (numpy.matrix): Sample from p(x).
|
||||
y (numpy.matrix): Sample from q(x).
|
||||
alpha (float): Mixture parameter.
|
||||
sigma_range (list<float>): Search range of Gaussian kernel bandwidth.
|
||||
lambda_range (list<float>): Search range of regularization parameter.
|
||||
kernel_num (int): Number of kernels. (Default 100)
|
||||
verbose (bool): Indicator to print messages (Default True)
|
||||
|
||||
Returns:
|
||||
densratio.DensityRatio object which has `compute_density_ratio()`.
|
||||
"""
|
||||
|
||||
# Number of samples.
|
||||
nx = x.shape[0]
|
||||
ny = y.shape[0]
|
||||
|
||||
# Number of kernel functions.
|
||||
kernel_num = min(kernel_num, nx)
|
||||
|
||||
# Randomly take a subset of x, to identify centers for the kernels.
|
||||
centers = x[randint(nx, size=kernel_num)]
|
||||
|
||||
if verbose:
|
||||
print("RuLSIF starting...")
|
||||
|
||||
if len(sigma_range) == 1 and len(lambda_range) == 1:
|
||||
sigma = sigma_range[0]
|
||||
lambda_ = lambda_range[0]
|
||||
else:
|
||||
if verbose:
|
||||
print("Searching for the optimal sigma and lambda...")
|
||||
|
||||
# Grid-search cross-validation for optimal kernel and regularization parameters.
|
||||
opt_params = search_sigma_and_lambda(
|
||||
x, y, alpha, centers, sigma_range, lambda_range, verbose
|
||||
)
|
||||
sigma = opt_params["sigma"]
|
||||
lambda_ = opt_params["lambda"]
|
||||
|
||||
if verbose:
|
||||
print(
|
||||
"Found optimal sigma = {:.3f}, lambda = {:.3f}.".format(sigma, lambda_)
|
||||
)
|
||||
|
||||
if verbose:
|
||||
print("Optimizing theta...")
|
||||
|
||||
phi_x = compute_kernel_Gaussian(x, centers, sigma)
|
||||
phi_y = compute_kernel_Gaussian(y, centers, sigma)
|
||||
H = alpha * (phi_x.T.dot(phi_x) / nx) + (1 - alpha) * (phi_y.T.dot(phi_y) / ny)
|
||||
h = phi_x.mean(axis=0).T
|
||||
theta = asarray(solve(H + diag(array(lambda_).repeat(kernel_num)), h)).ravel()
|
||||
|
||||
# No negative coefficients.
|
||||
theta[theta < 0] = 0
|
||||
|
||||
# Compute the alpha-relative density ratio, at the given coordinates.
|
||||
def alpha_density_ratio(coordinates):
|
||||
# Evaluate the kernel at these coordinates, and take the dot-product with the weights.
|
||||
coordinates = to_ndarray(coordinates)
|
||||
phi_x = compute_kernel_Gaussian(coordinates, centers, sigma)
|
||||
alpha_density_ratio = phi_x @ theta
|
||||
|
||||
return alpha_density_ratio
|
||||
|
||||
# Compute the approximate alpha-relative PE-divergence, given samples x and y from the respective distributions.
|
||||
def alpha_PE_divergence(x, y):
|
||||
# This is Y, in Reference 1.
|
||||
x = to_ndarray(x)
|
||||
|
||||
# Obtain alpha-relative density ratio at these points.
|
||||
g_x = alpha_density_ratio(x)
|
||||
|
||||
# This is Y', in Reference 1.
|
||||
y = to_ndarray(y)
|
||||
|
||||
# Obtain alpha-relative density ratio at these points.
|
||||
g_y = alpha_density_ratio(y)
|
||||
|
||||
# Compute the alpha-relative PE-divergence as given in Reference 1.
|
||||
n = x.shape[0]
|
||||
divergence = (
|
||||
-alpha * (g_x @ g_x) / 2 - (1 - alpha) * (g_y @ g_y) / 2 + g_x.sum(axis=0)
|
||||
) / n - 1.0 / 2
|
||||
return divergence
|
||||
|
||||
# Compute the approximate alpha-relative KL-divergence, given samples x and y from the respective distributions.
|
||||
def alpha_KL_divergence(x, y):
|
||||
# This is Y, in Reference 1.
|
||||
x = to_ndarray(x)
|
||||
|
||||
# Obtain alpha-relative density ratio at these points.
|
||||
g_x = alpha_density_ratio(x)
|
||||
|
||||
# Compute the alpha-relative KL-divergence.
|
||||
n = x.shape[0]
|
||||
divergence = log(g_x).sum(axis=0) / n
|
||||
return divergence
|
||||
|
||||
alpha_PE = alpha_PE_divergence(x, y)
|
||||
alpha_KL = alpha_KL_divergence(x, y)
|
||||
|
||||
if verbose:
|
||||
print("Approximate alpha-relative PE-divergence = {:03.2f}".format(alpha_PE))
|
||||
print("Approximate alpha-relative KL-divergence = {:03.2f}".format(alpha_KL))
|
||||
|
||||
kernel_info = KernelInfo(
|
||||
kernel_type="Gaussian", kernel_num=kernel_num, sigma=sigma, centers=centers
|
||||
)
|
||||
result = DensityRatio(
|
||||
method="RuLSIF",
|
||||
alpha=alpha,
|
||||
theta=theta,
|
||||
lambda_=lambda_,
|
||||
alpha_PE=alpha_PE,
|
||||
alpha_KL=alpha_KL,
|
||||
kernel_info=kernel_info,
|
||||
compute_density_ratio=alpha_density_ratio,
|
||||
)
|
||||
|
||||
if verbose:
|
||||
print("RuLSIF completed.")
|
||||
|
||||
return result
|
||||
|
||||
|
||||
# Grid-search cross-validation for the optimal parameters sigma and lambda by leave-one-out cross-validation. See Reference 2.
|
||||
def search_sigma_and_lambda(x, y, alpha, centers, sigma_range, lambda_range, verbose):
|
||||
nx = x.shape[0]
|
||||
ny = y.shape[0]
|
||||
n_min = min(nx, ny)
|
||||
kernel_num = centers.shape[0]
|
||||
|
||||
score_new = inf
|
||||
sigma_new = 0
|
||||
lambda_new = 0
|
||||
|
||||
for sigma in sigma_range:
|
||||
phi_x = compute_kernel_Gaussian(x, centers, sigma) # (nx, kernel_num)
|
||||
phi_y = compute_kernel_Gaussian(y, centers, sigma) # (ny, kernel_num)
|
||||
H = alpha * (phi_x.T @ phi_x / nx) + (1 - alpha) * (
|
||||
phi_y.T @ phi_y / ny
|
||||
) # (kernel_num, kernel_num)
|
||||
h = phi_x.mean(axis=0).reshape(-1, 1) # (kernel_num, 1)
|
||||
phi_x = phi_x[:n_min].T # (kernel_num, n_min)
|
||||
phi_y = phi_y[:n_min].T # (kernel_num, n_min)
|
||||
|
||||
for lambda_ in lambda_range:
|
||||
B = H + diag(
|
||||
array(lambda_ * (ny - 1) / ny).repeat(kernel_num)
|
||||
) # (kernel_num, kernel_num)
|
||||
B_inv_X = solve(B, phi_y) # (kernel_num, n_min)
|
||||
X_B_inv_X = multiply(phi_y, B_inv_X) # (kernel_num, n_min)
|
||||
denom = ny * ones(n_min) - ones(kernel_num) @ X_B_inv_X # (n_min, )
|
||||
B0 = solve(B, h @ ones((1, n_min))) + B_inv_X @ diagflat(
|
||||
h.T @ B_inv_X / denom
|
||||
) # (kernel_num, n_min)
|
||||
B1 = solve(B, phi_x) + B_inv_X @ diagflat(
|
||||
ones(kernel_num) @ multiply(phi_x, B_inv_X)
|
||||
) # (kernel_num, n_min)
|
||||
B2 = (ny - 1) * (nx * B0 - B1) / (ny * (nx - 1)) # (kernel_num, n_min)
|
||||
B2[B2 < 0] = 0
|
||||
r_y = multiply(phi_y, B2).sum(axis=0).T # (n_min, )
|
||||
r_x = multiply(phi_x, B2).sum(axis=0).T # (n_min, )
|
||||
|
||||
# Squared loss of RuLSIF, without regularization term.
|
||||
# Directly related to the negative of the PE-divergence.
|
||||
score = (r_y @ r_y / 2 - r_x.sum(axis=0)) / n_min
|
||||
|
||||
if verbose:
|
||||
print(
|
||||
"sigma = %.5f, lambda = %.5f, score = %.5f"
|
||||
% (sigma, lambda_, score)
|
||||
)
|
||||
|
||||
if score < score_new:
|
||||
score_new = score
|
||||
sigma_new = sigma
|
||||
lambda_new = lambda_
|
||||
|
||||
return {"sigma": sigma_new, "lambda": lambda_new}
|
||||
|
||||
|
||||
def _compute_kernel_Gaussian(x_list, y_row, neg_gamma, res) -> None:
|
||||
sq_norm = sum(power(x_list - y_row, 2), 1)
|
||||
multiply(neg_gamma, sq_norm, res)
|
||||
exp(res, res)
|
||||
|
||||
|
||||
def _target_numpy_wrapper(x_list, y_list, neg_gamma):
|
||||
res = empty((y_list.shape[0], x_list.shape[0]), np_float)
|
||||
if isinstance(x_list, matrix) or isinstance(y_list, matrix):
|
||||
res = asmatrix(res)
|
||||
|
||||
for j, y_row in enumerate(y_list):
|
||||
# `.T` aligns shapes for matrices, does nothing for 1D ndarray.
|
||||
_compute_kernel_Gaussian(x_list, y_row, neg_gamma, res[j].T)
|
||||
|
||||
return res
|
||||
|
||||
|
||||
_compute_functions = {"numpy": _target_numpy_wrapper}
|
||||
if guvectorize_compute:
|
||||
_compute_functions.update(
|
||||
{
|
||||
key: guvectorize_compute(key)(_compute_kernel_Gaussian)
|
||||
for key in ("cpu", "parallel")
|
||||
}
|
||||
)
|
||||
|
||||
_compute_function = _compute_functions[
|
||||
"cpu" if "cpu" in _compute_functions else "numpy"
|
||||
]
|
||||
|
||||
|
||||
# Returns a 2D numpy matrix of kernel evaluated at the gridpoints with coordinates from x_list and y_list.
|
||||
def compute_kernel_Gaussian(x_list, y_list, sigma):
|
||||
return _compute_function(x_list, y_list, -0.5 * sigma**-2).T
|
||||
|
||||
|
||||
def set_compute_kernel_target(target: str) -> None:
|
||||
global _compute_function
|
||||
if target not in ("numpy", "cpu", "parallel"):
|
||||
raise ValueError(
|
||||
"'target' must be one of the following: 'numpy', 'cpu', or 'parallel'."
|
||||
)
|
||||
|
||||
if target not in _compute_functions:
|
||||
warn("'numba' not available; defaulting to 'numpy'.", ImportWarning)
|
||||
target = "numpy"
|
||||
|
||||
_compute_function = _compute_functions[target]
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
from warnings import filterwarnings
|
||||
|
||||
from .core import densratio
|
||||
from .RuLSIF import set_compute_kernel_target
|
||||
|
||||
filterwarnings("default", message="'numba'", category=ImportWarning, module="densratio")
|
||||
__all__ = ["densratio", "set_compute_kernel_target"]
|
||||
from warnings import filterwarnings
|
||||
|
||||
from .core import densratio
|
||||
from .RuLSIF import set_compute_kernel_target
|
||||
|
||||
filterwarnings("default", message="'numba'", category=ImportWarning, module="densratio")
|
||||
__all__ = ["densratio", "set_compute_kernel_target"]
|
||||
|
|
|
|||
|
|
@ -1,70 +1,70 @@
|
|||
"""
|
||||
densratio.core
|
||||
~~~~~~~~~~~~~~
|
||||
|
||||
Estimate Density Ratio p(x)/q(y)
|
||||
"""
|
||||
|
||||
from numpy import linspace
|
||||
|
||||
from .helpers import to_ndarray
|
||||
from .RuLSIF import RuLSIF
|
||||
|
||||
|
||||
def densratio(
|
||||
x, y, alpha=0, sigma_range="auto", lambda_range="auto", kernel_num=100, verbose=True
|
||||
):
|
||||
"""Estimate alpha-mixture Density Ratio p(x)/(alpha*p(x) + (1 - alpha)*q(x))
|
||||
|
||||
Arguments:
|
||||
x: sample from p(x).
|
||||
y: sample from q(x).
|
||||
alpha: Default 0 - corresponds to ordinary density ratio.
|
||||
sigma_range: search range of Gaussian kernel bandwidth.
|
||||
Default "auto" means 10^-3, 10^-2, ..., 10^9.
|
||||
lambda_range: search range of regularization parameter for uLSIF.
|
||||
Default "auto" means 10^-3, 10^-2, ..., 10^9.
|
||||
kernel_num: number of kernels. Default 100.
|
||||
verbose: indicator to print messages. Default True.
|
||||
|
||||
Returns:
|
||||
densratio.DensityRatio object which has `compute_density_ratio()`.
|
||||
|
||||
Raises:
|
||||
ValueError: if dimension of x != dimension of y
|
||||
|
||||
Usage::
|
||||
>>> from scipy.stats import norm
|
||||
>>> from densratio import densratio
|
||||
|
||||
>>> x = norm.rvs(size=200, loc=1, scale=1./8)
|
||||
>>> y = norm.rvs(size=200, loc=1, scale=1./2)
|
||||
>>> result = densratio(x, y, alpha=0.7)
|
||||
>>> print(result)
|
||||
|
||||
>>> density_ratio = result.compute_density_ratio(y)
|
||||
>>> print(density_ratio)
|
||||
"""
|
||||
|
||||
x = to_ndarray(x)
|
||||
y = to_ndarray(y)
|
||||
|
||||
if x.shape[1] != y.shape[1]:
|
||||
raise ValueError("x and y must be same dimensions.")
|
||||
|
||||
if isinstance(sigma_range, str) and sigma_range != "auto":
|
||||
raise TypeError("Invalid value for sigma_range.")
|
||||
|
||||
if isinstance(lambda_range, str) and lambda_range != "auto":
|
||||
raise TypeError("Invalid value for lambda_range.")
|
||||
|
||||
if sigma_range is None or (isinstance(sigma_range, str) and sigma_range == "auto"):
|
||||
sigma_range = 10 ** linspace(-3, 9, 13)
|
||||
|
||||
if lambda_range is None or (
|
||||
isinstance(lambda_range, str) and lambda_range == "auto"
|
||||
):
|
||||
lambda_range = 10 ** linspace(-3, 9, 13)
|
||||
|
||||
result = RuLSIF(x, y, alpha, sigma_range, lambda_range, kernel_num, verbose)
|
||||
return result
|
||||
"""
|
||||
densratio.core
|
||||
~~~~~~~~~~~~~~
|
||||
|
||||
Estimate Density Ratio p(x)/q(y)
|
||||
"""
|
||||
|
||||
from numpy import linspace
|
||||
|
||||
from .helpers import to_ndarray
|
||||
from .RuLSIF import RuLSIF
|
||||
|
||||
|
||||
def densratio(
|
||||
x, y, alpha=0, sigma_range="auto", lambda_range="auto", kernel_num=100, verbose=True
|
||||
):
|
||||
"""Estimate alpha-mixture Density Ratio p(x)/(alpha*p(x) + (1 - alpha)*q(x))
|
||||
|
||||
Arguments:
|
||||
x: sample from p(x).
|
||||
y: sample from q(x).
|
||||
alpha: Default 0 - corresponds to ordinary density ratio.
|
||||
sigma_range: search range of Gaussian kernel bandwidth.
|
||||
Default "auto" means 10^-3, 10^-2, ..., 10^9.
|
||||
lambda_range: search range of regularization parameter for uLSIF.
|
||||
Default "auto" means 10^-3, 10^-2, ..., 10^9.
|
||||
kernel_num: number of kernels. Default 100.
|
||||
verbose: indicator to print messages. Default True.
|
||||
|
||||
Returns:
|
||||
densratio.DensityRatio object which has `compute_density_ratio()`.
|
||||
|
||||
Raises:
|
||||
ValueError: if dimension of x != dimension of y
|
||||
|
||||
Usage::
|
||||
>>> from scipy.stats import norm
|
||||
>>> from densratio import densratio
|
||||
|
||||
>>> x = norm.rvs(size=200, loc=1, scale=1./8)
|
||||
>>> y = norm.rvs(size=200, loc=1, scale=1./2)
|
||||
>>> result = densratio(x, y, alpha=0.7)
|
||||
>>> print(result)
|
||||
|
||||
>>> density_ratio = result.compute_density_ratio(y)
|
||||
>>> print(density_ratio)
|
||||
"""
|
||||
|
||||
x = to_ndarray(x)
|
||||
y = to_ndarray(y)
|
||||
|
||||
if x.shape[1] != y.shape[1]:
|
||||
raise ValueError("x and y must be same dimensions.")
|
||||
|
||||
if isinstance(sigma_range, str) and sigma_range != "auto":
|
||||
raise TypeError("Invalid value for sigma_range.")
|
||||
|
||||
if isinstance(lambda_range, str) and lambda_range != "auto":
|
||||
raise TypeError("Invalid value for lambda_range.")
|
||||
|
||||
if sigma_range is None or (isinstance(sigma_range, str) and sigma_range == "auto"):
|
||||
sigma_range = 10 ** linspace(-3, 9, 13)
|
||||
|
||||
if lambda_range is None or (
|
||||
isinstance(lambda_range, str) and lambda_range == "auto"
|
||||
):
|
||||
lambda_range = 10 ** linspace(-3, 9, 13)
|
||||
|
||||
result = RuLSIF(x, y, alpha, sigma_range, lambda_range, kernel_num, verbose)
|
||||
return result
|
||||
|
|
|
|||
|
|
@ -1,88 +1,88 @@
|
|||
from pprint import pformat
|
||||
from re import sub
|
||||
|
||||
|
||||
class DensityRatio:
|
||||
"""Density Ratio."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
method,
|
||||
alpha,
|
||||
theta,
|
||||
lambda_,
|
||||
alpha_PE,
|
||||
alpha_KL,
|
||||
kernel_info,
|
||||
compute_density_ratio,
|
||||
):
|
||||
self.method = method
|
||||
self.alpha = alpha
|
||||
self.theta = theta
|
||||
self.lambda_ = lambda_
|
||||
self.alpha_PE = alpha_PE
|
||||
self.alpha_KL = alpha_KL
|
||||
self.kernel_info = kernel_info
|
||||
self.compute_density_ratio = compute_density_ratio
|
||||
|
||||
def __str__(self):
|
||||
return """
|
||||
Method: %(method)s
|
||||
|
||||
Alpha: %(alpha)s
|
||||
|
||||
Kernel Information:
|
||||
%(kernel_info)s
|
||||
|
||||
Kernel Weights (theta):
|
||||
%(theta)s
|
||||
|
||||
Regularization Parameter (lambda): %(lambda_)s
|
||||
|
||||
Alpha-Relative PE-Divergence: %(alpha_PE)s
|
||||
|
||||
Alpha-Relative KL-Divergence: %(alpha_KL)s
|
||||
|
||||
Function to Estimate Density Ratio:
|
||||
compute_density_ratio(x)
|
||||
|
||||
"""[
|
||||
1:-1
|
||||
] % dict(
|
||||
method=self.method,
|
||||
kernel_info=self.kernel_info,
|
||||
alpha=self.alpha,
|
||||
theta=my_format(self.theta),
|
||||
lambda_=self.lambda_,
|
||||
alpha_PE=self.alpha_PE,
|
||||
alpha_KL=self.alpha_KL,
|
||||
)
|
||||
|
||||
|
||||
class KernelInfo:
|
||||
"""Kernel Information."""
|
||||
|
||||
def __init__(self, kernel_type, kernel_num, sigma, centers):
|
||||
self.kernel_type = kernel_type
|
||||
self.kernel_num = kernel_num
|
||||
self.sigma = sigma
|
||||
self.centers = centers
|
||||
|
||||
def __str__(self):
|
||||
return """
|
||||
Kernel type: %(kernel_type)s
|
||||
Number of kernels: %(kernel_num)s
|
||||
Bandwidth(sigma): %(sigma)s
|
||||
Centers: %(centers)s
|
||||
"""[
|
||||
1:-1
|
||||
] % dict(
|
||||
kernel_type=self.kernel_type,
|
||||
kernel_num=self.kernel_num,
|
||||
sigma=self.sigma,
|
||||
centers=my_format(self.centers),
|
||||
)
|
||||
|
||||
|
||||
def my_format(str):
|
||||
return sub(r"\s+", " ", (pformat(str).split("\n")[0] + ".."))
|
||||
from pprint import pformat
|
||||
from re import sub
|
||||
|
||||
|
||||
class DensityRatio:
|
||||
"""Density Ratio."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
method,
|
||||
alpha,
|
||||
theta,
|
||||
lambda_,
|
||||
alpha_PE,
|
||||
alpha_KL,
|
||||
kernel_info,
|
||||
compute_density_ratio,
|
||||
):
|
||||
self.method = method
|
||||
self.alpha = alpha
|
||||
self.theta = theta
|
||||
self.lambda_ = lambda_
|
||||
self.alpha_PE = alpha_PE
|
||||
self.alpha_KL = alpha_KL
|
||||
self.kernel_info = kernel_info
|
||||
self.compute_density_ratio = compute_density_ratio
|
||||
|
||||
def __str__(self):
|
||||
return """
|
||||
Method: %(method)s
|
||||
|
||||
Alpha: %(alpha)s
|
||||
|
||||
Kernel Information:
|
||||
%(kernel_info)s
|
||||
|
||||
Kernel Weights (theta):
|
||||
%(theta)s
|
||||
|
||||
Regularization Parameter (lambda): %(lambda_)s
|
||||
|
||||
Alpha-Relative PE-Divergence: %(alpha_PE)s
|
||||
|
||||
Alpha-Relative KL-Divergence: %(alpha_KL)s
|
||||
|
||||
Function to Estimate Density Ratio:
|
||||
compute_density_ratio(x)
|
||||
|
||||
"""[
|
||||
1:-1
|
||||
] % dict(
|
||||
method=self.method,
|
||||
kernel_info=self.kernel_info,
|
||||
alpha=self.alpha,
|
||||
theta=my_format(self.theta),
|
||||
lambda_=self.lambda_,
|
||||
alpha_PE=self.alpha_PE,
|
||||
alpha_KL=self.alpha_KL,
|
||||
)
|
||||
|
||||
|
||||
class KernelInfo:
|
||||
"""Kernel Information."""
|
||||
|
||||
def __init__(self, kernel_type, kernel_num, sigma, centers):
|
||||
self.kernel_type = kernel_type
|
||||
self.kernel_num = kernel_num
|
||||
self.sigma = sigma
|
||||
self.centers = centers
|
||||
|
||||
def __str__(self):
|
||||
return """
|
||||
Kernel type: %(kernel_type)s
|
||||
Number of kernels: %(kernel_num)s
|
||||
Bandwidth(sigma): %(sigma)s
|
||||
Centers: %(centers)s
|
||||
"""[
|
||||
1:-1
|
||||
] % dict(
|
||||
kernel_type=self.kernel_type,
|
||||
kernel_num=self.kernel_num,
|
||||
sigma=self.sigma,
|
||||
centers=my_format(self.centers),
|
||||
)
|
||||
|
||||
|
||||
def my_format(str):
|
||||
return sub(r"\s+", " ", (pformat(str).split("\n")[0] + ".."))
|
||||
|
|
|
|||
|
|
@ -1,36 +1,36 @@
|
|||
from numpy import array, ndarray, result_type
|
||||
|
||||
np_float = result_type(float)
|
||||
try:
|
||||
import numba as nb
|
||||
except ModuleNotFoundError:
|
||||
guvectorize_compute = None
|
||||
else:
|
||||
_nb_float = nb.from_dtype(np_float)
|
||||
|
||||
def guvectorize_compute(target: str, *, cache: bool = True):
|
||||
return nb.guvectorize(
|
||||
[nb.void(_nb_float[:, :], _nb_float[:], _nb_float, _nb_float[:])],
|
||||
"(m, p),(p),()->(m)",
|
||||
nopython=True,
|
||||
target=target,
|
||||
cache=cache,
|
||||
)
|
||||
|
||||
|
||||
def is_numeric(x):
|
||||
return isinstance(x, int) or isinstance(x, float)
|
||||
|
||||
|
||||
def to_ndarray(x):
|
||||
if isinstance(x, ndarray):
|
||||
if len(x.shape) == 1:
|
||||
return x.reshape(-1, 1)
|
||||
else:
|
||||
return x
|
||||
elif str(type(x)) == "<class 'pandas.core.frame.DataFrame'>":
|
||||
return x.values
|
||||
elif not x:
|
||||
raise ValueError("Cannot transform to numpy.matrix.")
|
||||
else:
|
||||
return to_ndarray(array(x))
|
||||
from numpy import array, ndarray, result_type
|
||||
|
||||
np_float = result_type(float)
|
||||
try:
|
||||
import numba as nb
|
||||
except ModuleNotFoundError:
|
||||
guvectorize_compute = None
|
||||
else:
|
||||
_nb_float = nb.from_dtype(np_float)
|
||||
|
||||
def guvectorize_compute(target: str, *, cache: bool = True):
|
||||
return nb.guvectorize(
|
||||
[nb.void(_nb_float[:, :], _nb_float[:], _nb_float, _nb_float[:])],
|
||||
"(m, p),(p),()->(m)",
|
||||
nopython=True,
|
||||
target=target,
|
||||
cache=cache,
|
||||
)
|
||||
|
||||
|
||||
def is_numeric(x):
|
||||
return isinstance(x, int) or isinstance(x, float)
|
||||
|
||||
|
||||
def to_ndarray(x):
|
||||
if isinstance(x, ndarray):
|
||||
if len(x.shape) == 1:
|
||||
return x.reshape(-1, 1)
|
||||
else:
|
||||
return x
|
||||
elif str(type(x)) == "<class 'pandas.core.frame.DataFrame'>":
|
||||
return x.values
|
||||
elif not x:
|
||||
raise ValueError("Cannot transform to numpy.matrix.")
|
||||
else:
|
||||
return to_ndarray(array(x))
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
import numpy as np
|
||||
|
||||
def get_doc(probs1, probs2):
|
||||
import numpy as np
|
||||
|
||||
def get_doc(probs1, probs2):
|
||||
return np.mean(probs2) - np.mean(probs1)
|
||||
|
|
@ -1,66 +1,66 @@
|
|||
import numpy as np
|
||||
from scipy.sparse import issparse, vstack
|
||||
from sklearn.linear_model import LogisticRegression
|
||||
from sklearn.model_selection import GridSearchCV
|
||||
from sklearn.neighbors import KernelDensity
|
||||
|
||||
from baselines import densratio
|
||||
from baselines.pykliep import DensityRatioEstimator
|
||||
|
||||
|
||||
def kliep(Xtr, ytr, Xte):
|
||||
kliep = DensityRatioEstimator()
|
||||
kliep.fit(Xtr, Xte)
|
||||
return kliep.predict(Xtr)
|
||||
|
||||
|
||||
def usilf(Xtr, ytr, Xte, alpha=0.0):
|
||||
dense_ratio_obj = densratio(Xtr, Xte, alpha=alpha, verbose=False)
|
||||
return dense_ratio_obj.compute_density_ratio(Xtr)
|
||||
|
||||
|
||||
def logreg(Xtr, ytr, Xte):
|
||||
# check "Direct Density Ratio Estimation for
|
||||
# Large-scale Covariate Shift Adaptation", Eq.28
|
||||
|
||||
if issparse(Xtr):
|
||||
X = vstack([Xtr, Xte])
|
||||
else:
|
||||
X = np.concatenate([Xtr, Xte])
|
||||
|
||||
y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
|
||||
|
||||
logreg = GridSearchCV(
|
||||
LogisticRegression(),
|
||||
param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
|
||||
n_jobs=-1,
|
||||
)
|
||||
logreg.fit(X, y)
|
||||
probs = logreg.predict_proba(Xtr)
|
||||
prob_train, prob_test = probs[:, 0], probs[:, 1]
|
||||
prior_train = Xtr.shape[0]
|
||||
prior_test = Xte.shape[0]
|
||||
w = (prior_train / prior_test) * (prob_test / prob_train)
|
||||
return w
|
||||
|
||||
|
||||
kdex2_params = {"bandwidth": np.logspace(-1, 1, 20)}
|
||||
|
||||
|
||||
def kdex2_lltr(Xtr):
|
||||
if issparse(Xtr):
|
||||
Xtr = Xtr.toarray()
|
||||
return GridSearchCV(KernelDensity(), kdex2_params).fit(Xtr).score_samples(Xtr)
|
||||
|
||||
|
||||
def kdex2_weights(Xtr, Xte, log_likelihood_tr):
|
||||
log_likelihood_te = (
|
||||
GridSearchCV(KernelDensity(), kdex2_params).fit(Xte).score_samples(Xtr)
|
||||
)
|
||||
likelihood_tr = np.exp(log_likelihood_tr)
|
||||
likelihood_te = np.exp(log_likelihood_te)
|
||||
return likelihood_te / likelihood_tr
|
||||
|
||||
|
||||
def get_acc(tr_preds, ytr, w):
|
||||
return np.sum((1.0 * (tr_preds == ytr)) * w) / np.sum(w)
|
||||
import numpy as np
|
||||
from scipy.sparse import issparse, vstack
|
||||
from sklearn.linear_model import LogisticRegression
|
||||
from sklearn.model_selection import GridSearchCV
|
||||
from sklearn.neighbors import KernelDensity
|
||||
|
||||
from baselines import densratio
|
||||
from baselines.pykliep import DensityRatioEstimator
|
||||
|
||||
|
||||
def kliep(Xtr, ytr, Xte):
|
||||
kliep = DensityRatioEstimator()
|
||||
kliep.fit(Xtr, Xte)
|
||||
return kliep.predict(Xtr)
|
||||
|
||||
|
||||
def usilf(Xtr, ytr, Xte, alpha=0.0):
|
||||
dense_ratio_obj = densratio(Xtr, Xte, alpha=alpha, verbose=False)
|
||||
return dense_ratio_obj.compute_density_ratio(Xtr)
|
||||
|
||||
|
||||
def logreg(Xtr, ytr, Xte):
|
||||
# check "Direct Density Ratio Estimation for
|
||||
# Large-scale Covariate Shift Adaptation", Eq.28
|
||||
|
||||
if issparse(Xtr):
|
||||
X = vstack([Xtr, Xte])
|
||||
else:
|
||||
X = np.concatenate([Xtr, Xte])
|
||||
|
||||
y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
|
||||
|
||||
logreg = GridSearchCV(
|
||||
LogisticRegression(),
|
||||
param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
|
||||
n_jobs=-1,
|
||||
)
|
||||
logreg.fit(X, y)
|
||||
probs = logreg.predict_proba(Xtr)
|
||||
prob_train, prob_test = probs[:, 0], probs[:, 1]
|
||||
prior_train = Xtr.shape[0]
|
||||
prior_test = Xte.shape[0]
|
||||
w = (prior_train / prior_test) * (prob_test / prob_train)
|
||||
return w
|
||||
|
||||
|
||||
kdex2_params = {"bandwidth": np.logspace(-1, 1, 20)}
|
||||
|
||||
|
||||
def kdex2_lltr(Xtr):
|
||||
if issparse(Xtr):
|
||||
Xtr = Xtr.toarray()
|
||||
return GridSearchCV(KernelDensity(), kdex2_params).fit(Xtr).score_samples(Xtr)
|
||||
|
||||
|
||||
def kdex2_weights(Xtr, Xte, log_likelihood_tr):
|
||||
log_likelihood_te = (
|
||||
GridSearchCV(KernelDensity(), kdex2_params).fit(Xte).score_samples(Xtr)
|
||||
)
|
||||
likelihood_tr = np.exp(log_likelihood_tr)
|
||||
likelihood_te = np.exp(log_likelihood_te)
|
||||
return likelihood_te / likelihood_tr
|
||||
|
||||
|
||||
def get_acc(tr_preds, ytr, w):
|
||||
return np.sum((1.0 * (tr_preds == ytr)) * w) / np.sum(w)
|
||||
|
|
|
|||
|
|
@ -1,140 +1,140 @@
|
|||
# import itertools
|
||||
# from typing import Iterable
|
||||
|
||||
# import quapy as qp
|
||||
# import quapy.functional as F
|
||||
# from densratio import densratio
|
||||
# from quapy.method.aggregative import *
|
||||
# from quapy.protocol import (
|
||||
# AbstractStochasticSeededProtocol,
|
||||
# OnLabelledCollectionProtocol,
|
||||
# )
|
||||
# from scipy.sparse import issparse, vstack
|
||||
# from scipy.spatial.distance import cdist
|
||||
# from scipy.stats import multivariate_normal
|
||||
# from sklearn.linear_model import LogisticRegression
|
||||
# from sklearn.model_selection import GridSearchCV
|
||||
# from sklearn.neighbors import KernelDensity
|
||||
|
||||
import time
|
||||
|
||||
import numpy as np
|
||||
import sklearn.metrics as metrics
|
||||
from pykliep import DensityRatioEstimator
|
||||
from quapy.protocol import APP
|
||||
from scipy.sparse import issparse, vstack
|
||||
from sklearn.linear_model import LogisticRegression
|
||||
from sklearn.model_selection import GridSearchCV
|
||||
from sklearn.neighbors import KernelDensity
|
||||
|
||||
import baselines.impweight as iw
|
||||
from baselines.densratio import densratio
|
||||
from quacc.dataset import Dataset
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------------------
|
||||
# Methods of "importance weight", e.g., by ratio density estimation (KLIEP, SILF, LogReg)
|
||||
# ---------------------------------------------------------------------------------------
|
||||
class ImportanceWeight:
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
...
|
||||
|
||||
|
||||
class KLIEP(ImportanceWeight):
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
kliep = DensityRatioEstimator()
|
||||
kliep.fit(Xtr, Xte)
|
||||
return kliep.predict(Xtr)
|
||||
|
||||
|
||||
class USILF(ImportanceWeight):
|
||||
def __init__(self, alpha=0.0):
|
||||
self.alpha = alpha
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
dense_ratio_obj = densratio(Xtr, Xte, alpha=self.alpha, verbose=False)
|
||||
return dense_ratio_obj.compute_density_ratio(Xtr)
|
||||
|
||||
|
||||
class LogReg(ImportanceWeight):
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
# check "Direct Density Ratio Estimation for
|
||||
# Large-scale Covariate Shift Adaptation", Eq.28
|
||||
|
||||
if issparse(Xtr):
|
||||
X = vstack([Xtr, Xte])
|
||||
else:
|
||||
X = np.concatenate([Xtr, Xte])
|
||||
|
||||
y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
|
||||
|
||||
logreg = GridSearchCV(
|
||||
LogisticRegression(),
|
||||
param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
|
||||
n_jobs=-1,
|
||||
)
|
||||
logreg.fit(X, y)
|
||||
probs = logreg.predict_proba(Xtr)
|
||||
prob_train, prob_test = probs[:, 0], probs[:, 1]
|
||||
prior_train = Xtr.shape[0]
|
||||
prior_test = Xte.shape[0]
|
||||
w = (prior_train / prior_test) * (prob_test / prob_train)
|
||||
return w
|
||||
|
||||
|
||||
class KDEx2(ImportanceWeight):
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
params = {"bandwidth": np.logspace(-1, 1, 20)}
|
||||
log_likelihood_tr = (
|
||||
GridSearchCV(KernelDensity(), params).fit(Xtr).score_samples(Xtr)
|
||||
)
|
||||
log_likelihood_te = (
|
||||
GridSearchCV(KernelDensity(), params).fit(Xte).score_samples(Xtr)
|
||||
)
|
||||
likelihood_tr = np.exp(log_likelihood_tr)
|
||||
likelihood_te = np.exp(log_likelihood_te)
|
||||
return likelihood_te / likelihood_tr
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# d = Dataset("rcv1", target="CCAT").get_raw()
|
||||
d = Dataset("imdb", n_prevalences=1).get()[0]
|
||||
|
||||
tstart = time.time()
|
||||
lr = LogisticRegression()
|
||||
lr.fit(*d.train.Xy)
|
||||
val_preds = lr.predict(d.validation.X)
|
||||
protocol = APP(
|
||||
d.test,
|
||||
n_prevalences=21,
|
||||
repeats=1,
|
||||
sample_size=100,
|
||||
return_type="labelled_collection",
|
||||
)
|
||||
|
||||
results = []
|
||||
for sample in protocol():
|
||||
wx = iw.kliep(d.validation.X, d.validation.y, sample.X)
|
||||
test_preds = lr.predict(sample.X)
|
||||
estim_acc = np.sum((1.0 * (val_preds == d.validation.y)) * wx) / np.sum(wx)
|
||||
true_acc = metrics.accuracy_score(sample.y, test_preds)
|
||||
results.append((sample.prevalence(), estim_acc, true_acc))
|
||||
|
||||
tend = time.time()
|
||||
|
||||
for r in results:
|
||||
print(*r)
|
||||
|
||||
print(f"logreg finished [took {tend-tstart:.3f}s]")
|
||||
import win11toast
|
||||
|
||||
win11toast.notify("models.py", "Completed")
|
||||
# import itertools
|
||||
# from typing import Iterable
|
||||
|
||||
# import quapy as qp
|
||||
# import quapy.functional as F
|
||||
# from densratio import densratio
|
||||
# from quapy.method.aggregative import *
|
||||
# from quapy.protocol import (
|
||||
# AbstractStochasticSeededProtocol,
|
||||
# OnLabelledCollectionProtocol,
|
||||
# )
|
||||
# from scipy.sparse import issparse, vstack
|
||||
# from scipy.spatial.distance import cdist
|
||||
# from scipy.stats import multivariate_normal
|
||||
# from sklearn.linear_model import LogisticRegression
|
||||
# from sklearn.model_selection import GridSearchCV
|
||||
# from sklearn.neighbors import KernelDensity
|
||||
|
||||
import time
|
||||
|
||||
import numpy as np
|
||||
import sklearn.metrics as metrics
|
||||
from pykliep import DensityRatioEstimator
|
||||
from quapy.protocol import APP
|
||||
from scipy.sparse import issparse, vstack
|
||||
from sklearn.linear_model import LogisticRegression
|
||||
from sklearn.model_selection import GridSearchCV
|
||||
from sklearn.neighbors import KernelDensity
|
||||
|
||||
import baselines.impweight as iw
|
||||
from baselines.densratio import densratio
|
||||
from quacc.dataset import Dataset
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------------------
|
||||
# Methods of "importance weight", e.g., by ratio density estimation (KLIEP, SILF, LogReg)
|
||||
# ---------------------------------------------------------------------------------------
|
||||
class ImportanceWeight:
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
...
|
||||
|
||||
|
||||
class KLIEP(ImportanceWeight):
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
kliep = DensityRatioEstimator()
|
||||
kliep.fit(Xtr, Xte)
|
||||
return kliep.predict(Xtr)
|
||||
|
||||
|
||||
class USILF(ImportanceWeight):
|
||||
def __init__(self, alpha=0.0):
|
||||
self.alpha = alpha
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
dense_ratio_obj = densratio(Xtr, Xte, alpha=self.alpha, verbose=False)
|
||||
return dense_ratio_obj.compute_density_ratio(Xtr)
|
||||
|
||||
|
||||
class LogReg(ImportanceWeight):
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
# check "Direct Density Ratio Estimation for
|
||||
# Large-scale Covariate Shift Adaptation", Eq.28
|
||||
|
||||
if issparse(Xtr):
|
||||
X = vstack([Xtr, Xte])
|
||||
else:
|
||||
X = np.concatenate([Xtr, Xte])
|
||||
|
||||
y = [0] * Xtr.shape[0] + [1] * Xte.shape[0]
|
||||
|
||||
logreg = GridSearchCV(
|
||||
LogisticRegression(),
|
||||
param_grid={"C": np.logspace(-3, 3, 7), "class_weight": ["balanced", None]},
|
||||
n_jobs=-1,
|
||||
)
|
||||
logreg.fit(X, y)
|
||||
probs = logreg.predict_proba(Xtr)
|
||||
prob_train, prob_test = probs[:, 0], probs[:, 1]
|
||||
prior_train = Xtr.shape[0]
|
||||
prior_test = Xte.shape[0]
|
||||
w = (prior_train / prior_test) * (prob_test / prob_train)
|
||||
return w
|
||||
|
||||
|
||||
class KDEx2(ImportanceWeight):
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def weights(self, Xtr, ytr, Xte):
|
||||
params = {"bandwidth": np.logspace(-1, 1, 20)}
|
||||
log_likelihood_tr = (
|
||||
GridSearchCV(KernelDensity(), params).fit(Xtr).score_samples(Xtr)
|
||||
)
|
||||
log_likelihood_te = (
|
||||
GridSearchCV(KernelDensity(), params).fit(Xte).score_samples(Xtr)
|
||||
)
|
||||
likelihood_tr = np.exp(log_likelihood_tr)
|
||||
likelihood_te = np.exp(log_likelihood_te)
|
||||
return likelihood_te / likelihood_tr
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# d = Dataset("rcv1", target="CCAT").get_raw()
|
||||
d = Dataset("imdb", n_prevalences=1).get()[0]
|
||||
|
||||
tstart = time.time()
|
||||
lr = LogisticRegression()
|
||||
lr.fit(*d.train.Xy)
|
||||
val_preds = lr.predict(d.validation.X)
|
||||
protocol = APP(
|
||||
d.test,
|
||||
n_prevalences=21,
|
||||
repeats=1,
|
||||
sample_size=100,
|
||||
return_type="labelled_collection",
|
||||
)
|
||||
|
||||
results = []
|
||||
for sample in protocol():
|
||||
wx = iw.kliep(d.validation.X, d.validation.y, sample.X)
|
||||
test_preds = lr.predict(sample.X)
|
||||
estim_acc = np.sum((1.0 * (val_preds == d.validation.y)) * wx) / np.sum(wx)
|
||||
true_acc = metrics.accuracy_score(sample.y, test_preds)
|
||||
results.append((sample.prevalence(), estim_acc, true_acc))
|
||||
|
||||
tend = time.time()
|
||||
|
||||
for r in results:
|
||||
print(*r)
|
||||
|
||||
print(f"logreg finished [took {tend-tstart:.3f}s]")
|
||||
import win11toast
|
||||
|
||||
win11toast.notify("models.py", "Completed")
|
||||
|
|
|
|||
|
|
@ -1,221 +1,221 @@
|
|||
import warnings
|
||||
|
||||
import numpy as np
|
||||
from scipy.sparse import csr_matrix
|
||||
|
||||
|
||||
class DensityRatioEstimator:
|
||||
"""
|
||||
Class to accomplish direct density estimation implementing the original KLIEP
|
||||
algorithm from Direct Importance Estimation with Model Selection
|
||||
and Its Application to Covariate Shift Adaptation by Sugiyama et al.
|
||||
|
||||
The training set is distributed via
|
||||
train ~ p(x)
|
||||
and the test set is distributed via
|
||||
test ~ q(x).
|
||||
|
||||
The KLIEP algorithm and its variants approximate w(x) = q(x) / p(x) directly. The predict function returns the
|
||||
estimate of w(x). The function w(x) can serve as sample weights for the training set during
|
||||
training to modify the expectation function that the model's loss function is optimized via,
|
||||
i.e.
|
||||
|
||||
E_{x ~ w(x)p(x)} loss(x) = E_{x ~ q(x)} loss(x).
|
||||
|
||||
Usage :
|
||||
The fit method is used to run the KLIEP algorithm using LCV and returns value of J
|
||||
trained on the entire training/test set with the best sigma found.
|
||||
Use the predict method on the training set to determine the sample weights from the KLIEP algorithm.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
max_iter=5000,
|
||||
num_params=[0.1, 0.2],
|
||||
epsilon=1e-4,
|
||||
cv=3,
|
||||
sigmas=[0.01, 0.1, 0.25, 0.5, 0.75, 1],
|
||||
random_state=None,
|
||||
verbose=0,
|
||||
):
|
||||
"""
|
||||
Direct density estimation using an inner LCV loop to estimate the proper model. Can be used with sklearn
|
||||
cross validation methods with or without storing the inner CV. To use a standard grid search.
|
||||
|
||||
|
||||
max_iter : Number of iterations to perform
|
||||
num_params : List of number of test set vectors used to construct the approximation for inner LCV.
|
||||
Must be a float. Original paper used 10%, i.e. =.1
|
||||
sigmas : List of sigmas to be used in inner LCV loop.
|
||||
epsilon : Additive factor in the iterative algorithm for numerical stability.
|
||||
"""
|
||||
self.max_iter = max_iter
|
||||
self.num_params = num_params
|
||||
self.epsilon = epsilon
|
||||
self.verbose = verbose
|
||||
self.sigmas = sigmas
|
||||
self.cv = cv
|
||||
self.random_state = 0
|
||||
|
||||
def fit(self, X_train, X_test, alpha_0=None):
|
||||
"""Uses cross validation to select sigma as in the original paper (LCV).
|
||||
In a break from sklearn convention, y=X_test.
|
||||
The parameter cv corresponds to R in the original paper.
|
||||
Once found, the best sigma is used to train on the full set."""
|
||||
|
||||
# LCV loop, shuffle a copy in place for performance.
|
||||
cv = self.cv
|
||||
chunk = int(X_test.shape[0] / float(cv))
|
||||
if self.random_state is not None:
|
||||
np.random.seed(self.random_state)
|
||||
# if isinstance(X_test, csr_matrix):
|
||||
# X_test_shuffled = X_test.toarray()
|
||||
# else:
|
||||
# X_test_shuffled = X_test.copy()
|
||||
X_test_shuffled = X_test.copy()
|
||||
|
||||
X_test_index = np.arange(X_test_shuffled.shape[0])
|
||||
np.random.shuffle(X_test_index)
|
||||
X_test_shuffled = X_test_shuffled[X_test_index, :]
|
||||
|
||||
j_scores = {}
|
||||
|
||||
if type(self.sigmas) != list:
|
||||
self.sigmas = [self.sigmas]
|
||||
|
||||
if type(self.num_params) != list:
|
||||
self.num_params = [self.num_params]
|
||||
|
||||
if len(self.sigmas) * len(self.num_params) > 1:
|
||||
# Inner LCV loop
|
||||
for num_param in self.num_params:
|
||||
for sigma in self.sigmas:
|
||||
j_scores[(num_param, sigma)] = np.zeros(cv)
|
||||
for k in range(1, cv + 1):
|
||||
if self.verbose > 0:
|
||||
print("Training: sigma: %s R: %s" % (sigma, k))
|
||||
X_test_fold = X_test_shuffled[(k - 1) * chunk : k * chunk, :]
|
||||
j_scores[(num_param, sigma)][k - 1] = self._fit(
|
||||
X_train=X_train,
|
||||
X_test=X_test_fold,
|
||||
num_parameters=num_param,
|
||||
sigma=sigma,
|
||||
)
|
||||
j_scores[(num_param, sigma)] = np.mean(j_scores[(num_param, sigma)])
|
||||
|
||||
sorted_scores = sorted(
|
||||
[x for x in j_scores.items() if np.isfinite(x[1])],
|
||||
key=lambda x: x[1],
|
||||
reverse=True,
|
||||
)
|
||||
if len(sorted_scores) == 0:
|
||||
warnings.warn("LCV failed to converge for all values of sigma.")
|
||||
return self
|
||||
self._sigma = sorted_scores[0][0][1]
|
||||
self._num_parameters = sorted_scores[0][0][0]
|
||||
self._j_scores = sorted_scores
|
||||
else:
|
||||
self._sigma = self.sigmas[0]
|
||||
self._num_parameters = self.num_params[0]
|
||||
# best sigma
|
||||
self._j = self._fit(
|
||||
X_train=X_train,
|
||||
X_test=X_test_shuffled,
|
||||
num_parameters=self._num_parameters,
|
||||
sigma=self._sigma,
|
||||
)
|
||||
|
||||
return self # Compatibility with sklearn
|
||||
|
||||
def _fit(self, X_train, X_test, num_parameters, sigma, alpha_0=None):
|
||||
"""Fits the estimator with the given parameters w-hat and returns J"""
|
||||
|
||||
num_parameters = num_parameters
|
||||
|
||||
if type(num_parameters) == float:
|
||||
num_parameters = int(X_test.shape[0] * num_parameters)
|
||||
|
||||
self._select_param_vectors(
|
||||
X_test=X_test, sigma=sigma, num_parameters=num_parameters
|
||||
)
|
||||
|
||||
# if isinstance(X_train, csr_matrix):
|
||||
# X_train = X_train.toarray()
|
||||
X_train = self._reshape_X(X_train)
|
||||
X_test = self._reshape_X(X_test)
|
||||
|
||||
if alpha_0 is None:
|
||||
alpha_0 = np.ones(shape=(num_parameters, 1)) / float(num_parameters)
|
||||
|
||||
self._find_alpha(
|
||||
X_train=X_train,
|
||||
X_test=X_test,
|
||||
num_parameters=num_parameters,
|
||||
epsilon=self.epsilon,
|
||||
alpha_0=alpha_0,
|
||||
sigma=sigma,
|
||||
)
|
||||
|
||||
return self._calculate_j(X_test, sigma=sigma)
|
||||
|
||||
def _calculate_j(self, X_test, sigma):
|
||||
pred = self.predict(X_test, sigma=sigma) + 0.0000001
|
||||
log = np.log(pred).sum()
|
||||
return log / (X_test.shape[0])
|
||||
|
||||
def score(self, X_test):
|
||||
"""Return the J score, similar to sklearn's API"""
|
||||
return self._calculate_j(X_test=X_test, sigma=self._sigma)
|
||||
|
||||
@staticmethod
|
||||
def _reshape_X(X):
|
||||
"""Reshape input from mxn to mx1xn to take advantage of numpy broadcasting."""
|
||||
if len(X.shape) != 3:
|
||||
return X.reshape((X.shape[0], 1, X.shape[1]))
|
||||
return X
|
||||
|
||||
def _select_param_vectors(self, X_test, sigma, num_parameters):
|
||||
"""X_test is the test set. b is the number of parameters."""
|
||||
indices = np.random.choice(X_test.shape[0], size=num_parameters, replace=False)
|
||||
self._test_vectors = X_test[indices, :].copy()
|
||||
self._phi_fitted = True
|
||||
|
||||
def _phi(self, X, sigma=None):
|
||||
if sigma is None:
|
||||
sigma = self._sigma
|
||||
|
||||
if self._phi_fitted:
|
||||
return np.exp(
|
||||
-np.sum((X - self._test_vectors) ** 2, axis=-1) / (2 * sigma**2)
|
||||
)
|
||||
raise Exception("Phi not fitted.")
|
||||
|
||||
def _find_alpha(self, alpha_0, X_train, X_test, num_parameters, sigma, epsilon):
|
||||
A = np.zeros(shape=(X_test.shape[0], num_parameters))
|
||||
b = np.zeros(shape=(num_parameters, 1))
|
||||
|
||||
A = self._phi(X_test, sigma)
|
||||
b = self._phi(X_train, sigma).sum(axis=0) / X_train.shape[0]
|
||||
b = b.reshape((num_parameters, 1))
|
||||
|
||||
out = alpha_0.copy()
|
||||
for k in range(self.max_iter):
|
||||
mat = np.dot(A, out)
|
||||
mat += 0.000000001
|
||||
out += epsilon * np.dot(np.transpose(A), 1.0 / mat)
|
||||
out += b * (
|
||||
((1 - np.dot(np.transpose(b), out)) / np.dot(np.transpose(b), b))
|
||||
)
|
||||
out = np.maximum(0, out)
|
||||
out /= np.dot(np.transpose(b), out)
|
||||
|
||||
self._alpha = out
|
||||
self._fitted = True
|
||||
|
||||
def predict(self, X, sigma=None):
|
||||
"""Equivalent of w(X) from the original paper."""
|
||||
|
||||
X = self._reshape_X(X)
|
||||
if not self._fitted:
|
||||
raise Exception("Not fitted!")
|
||||
return np.dot(self._phi(X, sigma=sigma), self._alpha).reshape((X.shape[0],))
|
||||
import warnings
|
||||
|
||||
import numpy as np
|
||||
from scipy.sparse import csr_matrix
|
||||
|
||||
|
||||
class DensityRatioEstimator:
|
||||
"""
|
||||
Class to accomplish direct density estimation implementing the original KLIEP
|
||||
algorithm from Direct Importance Estimation with Model Selection
|
||||
and Its Application to Covariate Shift Adaptation by Sugiyama et al.
|
||||
|
||||
The training set is distributed via
|
||||
train ~ p(x)
|
||||
and the test set is distributed via
|
||||
test ~ q(x).
|
||||
|
||||
The KLIEP algorithm and its variants approximate w(x) = q(x) / p(x) directly. The predict function returns the
|
||||
estimate of w(x). The function w(x) can serve as sample weights for the training set during
|
||||
training to modify the expectation function that the model's loss function is optimized via,
|
||||
i.e.
|
||||
|
||||
E_{x ~ w(x)p(x)} loss(x) = E_{x ~ q(x)} loss(x).
|
||||
|
||||
Usage :
|
||||
The fit method is used to run the KLIEP algorithm using LCV and returns value of J
|
||||
trained on the entire training/test set with the best sigma found.
|
||||
Use the predict method on the training set to determine the sample weights from the KLIEP algorithm.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
max_iter=5000,
|
||||
num_params=[0.1, 0.2],
|
||||
epsilon=1e-4,
|
||||
cv=3,
|
||||
sigmas=[0.01, 0.1, 0.25, 0.5, 0.75, 1],
|
||||
random_state=None,
|
||||
verbose=0,
|
||||
):
|
||||
"""
|
||||
Direct density estimation using an inner LCV loop to estimate the proper model. Can be used with sklearn
|
||||
cross validation methods with or without storing the inner CV. To use a standard grid search.
|
||||
|
||||
|
||||
max_iter : Number of iterations to perform
|
||||
num_params : List of number of test set vectors used to construct the approximation for inner LCV.
|
||||
Must be a float. Original paper used 10%, i.e. =.1
|
||||
sigmas : List of sigmas to be used in inner LCV loop.
|
||||
epsilon : Additive factor in the iterative algorithm for numerical stability.
|
||||
"""
|
||||
self.max_iter = max_iter
|
||||
self.num_params = num_params
|
||||
self.epsilon = epsilon
|
||||
self.verbose = verbose
|
||||
self.sigmas = sigmas
|
||||
self.cv = cv
|
||||
self.random_state = 0
|
||||
|
||||
def fit(self, X_train, X_test, alpha_0=None):
|
||||
"""Uses cross validation to select sigma as in the original paper (LCV).
|
||||
In a break from sklearn convention, y=X_test.
|
||||
The parameter cv corresponds to R in the original paper.
|
||||
Once found, the best sigma is used to train on the full set."""
|
||||
|
||||
# LCV loop, shuffle a copy in place for performance.
|
||||
cv = self.cv
|
||||
chunk = int(X_test.shape[0] / float(cv))
|
||||
if self.random_state is not None:
|
||||
np.random.seed(self.random_state)
|
||||
# if isinstance(X_test, csr_matrix):
|
||||
# X_test_shuffled = X_test.toarray()
|
||||
# else:
|
||||
# X_test_shuffled = X_test.copy()
|
||||
X_test_shuffled = X_test.copy()
|
||||
|
||||
X_test_index = np.arange(X_test_shuffled.shape[0])
|
||||
np.random.shuffle(X_test_index)
|
||||
X_test_shuffled = X_test_shuffled[X_test_index, :]
|
||||
|
||||
j_scores = {}
|
||||
|
||||
if type(self.sigmas) != list:
|
||||
self.sigmas = [self.sigmas]
|
||||
|
||||
if type(self.num_params) != list:
|
||||
self.num_params = [self.num_params]
|
||||
|
||||
if len(self.sigmas) * len(self.num_params) > 1:
|
||||
# Inner LCV loop
|
||||
for num_param in self.num_params:
|
||||
for sigma in self.sigmas:
|
||||
j_scores[(num_param, sigma)] = np.zeros(cv)
|
||||
for k in range(1, cv + 1):
|
||||
if self.verbose > 0:
|
||||
print("Training: sigma: %s R: %s" % (sigma, k))
|
||||
X_test_fold = X_test_shuffled[(k - 1) * chunk : k * chunk, :]
|
||||
j_scores[(num_param, sigma)][k - 1] = self._fit(
|
||||
X_train=X_train,
|
||||
X_test=X_test_fold,
|
||||
num_parameters=num_param,
|
||||
sigma=sigma,
|
||||
)
|
||||
j_scores[(num_param, sigma)] = np.mean(j_scores[(num_param, sigma)])
|
||||
|
||||
sorted_scores = sorted(
|
||||
[x for x in j_scores.items() if np.isfinite(x[1])],
|
||||
key=lambda x: x[1],
|
||||
reverse=True,
|
||||
)
|
||||
if len(sorted_scores) == 0:
|
||||
warnings.warn("LCV failed to converge for all values of sigma.")
|
||||
return self
|
||||
self._sigma = sorted_scores[0][0][1]
|
||||
self._num_parameters = sorted_scores[0][0][0]
|
||||
self._j_scores = sorted_scores
|
||||
else:
|
||||
self._sigma = self.sigmas[0]
|
||||
self._num_parameters = self.num_params[0]
|
||||
# best sigma
|
||||
self._j = self._fit(
|
||||
X_train=X_train,
|
||||
X_test=X_test_shuffled,
|
||||
num_parameters=self._num_parameters,
|
||||
sigma=self._sigma,
|
||||
)
|
||||
|
||||
return self # Compatibility with sklearn
|
||||
|
||||
def _fit(self, X_train, X_test, num_parameters, sigma, alpha_0=None):
|
||||
"""Fits the estimator with the given parameters w-hat and returns J"""
|
||||
|
||||
num_parameters = num_parameters
|
||||
|
||||
if type(num_parameters) == float:
|
||||
num_parameters = int(X_test.shape[0] * num_parameters)
|
||||
|
||||
self._select_param_vectors(
|
||||
X_test=X_test, sigma=sigma, num_parameters=num_parameters
|
||||
)
|
||||
|
||||
# if isinstance(X_train, csr_matrix):
|
||||
# X_train = X_train.toarray()
|
||||
X_train = self._reshape_X(X_train)
|
||||
X_test = self._reshape_X(X_test)
|
||||
|
||||
if alpha_0 is None:
|
||||
alpha_0 = np.ones(shape=(num_parameters, 1)) / float(num_parameters)
|
||||
|
||||
self._find_alpha(
|
||||
X_train=X_train,
|
||||
X_test=X_test,
|
||||
num_parameters=num_parameters,
|
||||
epsilon=self.epsilon,
|
||||
alpha_0=alpha_0,
|
||||
sigma=sigma,
|
||||
)
|
||||
|
||||
return self._calculate_j(X_test, sigma=sigma)
|
||||
|
||||
def _calculate_j(self, X_test, sigma):
|
||||
pred = self.predict(X_test, sigma=sigma) + 0.0000001
|
||||
log = np.log(pred).sum()
|
||||
return log / (X_test.shape[0])
|
||||
|
||||
def score(self, X_test):
|
||||
"""Return the J score, similar to sklearn's API"""
|
||||
return self._calculate_j(X_test=X_test, sigma=self._sigma)
|
||||
|
||||
@staticmethod
|
||||
def _reshape_X(X):
|
||||
"""Reshape input from mxn to mx1xn to take advantage of numpy broadcasting."""
|
||||
if len(X.shape) != 3:
|
||||
return X.reshape((X.shape[0], 1, X.shape[1]))
|
||||
return X
|
||||
|
||||
def _select_param_vectors(self, X_test, sigma, num_parameters):
|
||||
"""X_test is the test set. b is the number of parameters."""
|
||||
indices = np.random.choice(X_test.shape[0], size=num_parameters, replace=False)
|
||||
self._test_vectors = X_test[indices, :].copy()
|
||||
self._phi_fitted = True
|
||||
|
||||
def _phi(self, X, sigma=None):
|
||||
if sigma is None:
|
||||
sigma = self._sigma
|
||||
|
||||
if self._phi_fitted:
|
||||
return np.exp(
|
||||
-np.sum((X - self._test_vectors) ** 2, axis=-1) / (2 * sigma**2)
|
||||
)
|
||||
raise Exception("Phi not fitted.")
|
||||
|
||||
def _find_alpha(self, alpha_0, X_train, X_test, num_parameters, sigma, epsilon):
|
||||
A = np.zeros(shape=(X_test.shape[0], num_parameters))
|
||||
b = np.zeros(shape=(num_parameters, 1))
|
||||
|
||||
A = self._phi(X_test, sigma)
|
||||
b = self._phi(X_train, sigma).sum(axis=0) / X_train.shape[0]
|
||||
b = b.reshape((num_parameters, 1))
|
||||
|
||||
out = alpha_0.copy()
|
||||
for k in range(self.max_iter):
|
||||
mat = np.dot(A, out)
|
||||
mat += 0.000000001
|
||||
out += epsilon * np.dot(np.transpose(A), 1.0 / mat)
|
||||
out += b * (
|
||||
((1 - np.dot(np.transpose(b), out)) / np.dot(np.transpose(b), b))
|
||||
)
|
||||
out = np.maximum(0, out)
|
||||
out /= np.dot(np.transpose(b), out)
|
||||
|
||||
self._alpha = out
|
||||
self._fitted = True
|
||||
|
||||
def predict(self, X, sigma=None):
|
||||
"""Equivalent of w(X) from the original paper."""
|
||||
|
||||
X = self._reshape_X(X)
|
||||
if not self._fitted:
|
||||
raise Exception("Not fitted!")
|
||||
return np.dot(self._phi(X, sigma=sigma), self._alpha).reshape((X.shape[0],))
|
||||
|
|
|
|||
|
|
@ -1,14 +1,14 @@
|
|||
import numpy as np
|
||||
from sklearn import clone
|
||||
from sklearn.base import BaseEstimator
|
||||
|
||||
|
||||
def clone_fit(c_model: BaseEstimator, data, labels):
|
||||
c_model2 = clone(c_model)
|
||||
c_model2.fit(data, labels)
|
||||
return c_model2
|
||||
|
||||
def get_score(pred1, pred2, labels):
|
||||
return np.mean((pred1 == labels).astype(int) - (pred2 == labels).astype(int))
|
||||
|
||||
|
||||
import numpy as np
|
||||
from sklearn import clone
|
||||
from sklearn.base import BaseEstimator
|
||||
|
||||
|
||||
def clone_fit(c_model: BaseEstimator, data, labels):
|
||||
c_model2 = clone(c_model)
|
||||
c_model2.fit(data, labels)
|
||||
return c_model2
|
||||
|
||||
def get_score(pred1, pred2, labels):
|
||||
return np.mean((pred1 == labels).astype(int) - (pred2 == labels).astype(int))
|
||||
|
||||
|
||||
|
|
|
|||
464
conf.yaml
464
conf.yaml
|
|
@ -1,233 +1,233 @@
|
|||
debug_conf: &debug_conf
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
DATASET_N_PREVS: 5
|
||||
DATASET_PREVS:
|
||||
# - 0.2
|
||||
- 0.5
|
||||
# - 0.8
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
|
||||
plot_confs:
|
||||
debug:
|
||||
PLOT_ESTIMATORS:
|
||||
- mulmc_sld
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
|
||||
mc_conf: &mc_conf
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
DATASET_N_PREVS: 9
|
||||
DATASET_DIR_UPDATE: true
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
# - DATASET_NAME: imdb
|
||||
|
||||
plot_confs:
|
||||
debug3:
|
||||
PLOT_ESTIMATORS:
|
||||
- binmc_sld
|
||||
- mulmc_sld
|
||||
- binne_sld
|
||||
- mulne_sld
|
||||
- bin_sld_gs
|
||||
- mul_sld_gs
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
|
||||
test_conf: &test_conf
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
- f1
|
||||
DATASET_N_PREVS: 9
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
# - DATASET_NAME: imdb
|
||||
|
||||
plot_confs:
|
||||
gs_vs_gsq:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_gs
|
||||
- bin_sld_gsq
|
||||
- mul_sld
|
||||
- mul_sld_gs
|
||||
- mul_sld_gsq
|
||||
gs_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_gs
|
||||
- mul_sld
|
||||
- mul_sld_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
sld_vs_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_gs
|
||||
- mul_sld
|
||||
- mul_sld_gs
|
||||
- bin_pacc
|
||||
- bin_pacc_gs
|
||||
- mul_pacc
|
||||
- mul_pacc_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
pacc_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_pacc
|
||||
- bin_pacc_gs
|
||||
- mul_pacc
|
||||
- mul_pacc_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
|
||||
main_conf: &main_conf
|
||||
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
- f1
|
||||
DATASET_N_PREVS: 9
|
||||
DATASET_DIR_UPDATE: true
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
- DATASET_NAME: imdb
|
||||
confs_next:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: GCAT
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: MCAT
|
||||
|
||||
plot_confs:
|
||||
gs_vs_qgs:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_sld_gsq
|
||||
- bin_sld_gsq
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
PLOT_STDEV: true
|
||||
plot_confs_completed:
|
||||
max_conf_vs_atc_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_pacc
|
||||
- binmc_pacc
|
||||
- mul_pacc
|
||||
- mulmc_pacc
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
max_conf_vs_entropy_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- binmc_pacc
|
||||
- binne_pacc
|
||||
- mulmc_pacc
|
||||
- mulne_pacc
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
gs_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_pacc_gs
|
||||
- bin_pacc_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
PLOT_STDEV: true
|
||||
gs_vs_all:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_pacc_gs
|
||||
- bin_pacc_gs
|
||||
- atc_mc
|
||||
- doc_feat
|
||||
- kfcv
|
||||
PLOT_STDEV: true
|
||||
gs_vs_qgs:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_sld_gsq
|
||||
- bin_sld_gsq
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
PLOT_STDEV: true
|
||||
cc_vs_other:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_cc
|
||||
- bin_cc
|
||||
- mul_sld
|
||||
- bin_sld
|
||||
- mul_pacc
|
||||
- bin_pacc
|
||||
PLOT_STDEV: true
|
||||
max_conf_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- binmc_sld
|
||||
- mul_sld
|
||||
- mulmc_sld
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
max_conf_vs_entropy:
|
||||
PLOT_ESTIMATORS:
|
||||
- binmc_sld
|
||||
- binne_sld
|
||||
- mulmc_sld
|
||||
- mulne_sld
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
sld_vs_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- mul_sld
|
||||
- bin_pacc
|
||||
- mul_pacc
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
plot_confs_other:
|
||||
best_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_bcts
|
||||
- mul_sld_gs
|
||||
- bin_sld_bcts
|
||||
- bin_sld_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
all_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_bcts
|
||||
- bin_sld_gs
|
||||
- mul_sld
|
||||
- mul_sld_bcts
|
||||
- mul_sld_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
best_vs_all:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld_bcts
|
||||
- bin_sld_gs
|
||||
- mul_sld_bcts
|
||||
- mul_sld_gs
|
||||
- kfcv
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
- doc_feat
|
||||
|
||||
debug_conf: &debug_conf
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
DATASET_N_PREVS: 5
|
||||
DATASET_PREVS:
|
||||
# - 0.2
|
||||
- 0.5
|
||||
# - 0.8
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
|
||||
plot_confs:
|
||||
debug:
|
||||
PLOT_ESTIMATORS:
|
||||
- mulmc_sld
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
|
||||
mc_conf: &mc_conf
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
DATASET_N_PREVS: 9
|
||||
DATASET_DIR_UPDATE: true
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
# - DATASET_NAME: imdb
|
||||
|
||||
plot_confs:
|
||||
debug3:
|
||||
PLOT_ESTIMATORS:
|
||||
- binmc_sld
|
||||
- mulmc_sld
|
||||
- binne_sld
|
||||
- mulne_sld
|
||||
- bin_sld_gs
|
||||
- mul_sld_gs
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
|
||||
test_conf: &test_conf
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
- f1
|
||||
DATASET_N_PREVS: 9
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
# - DATASET_NAME: imdb
|
||||
|
||||
plot_confs:
|
||||
gs_vs_gsq:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_gs
|
||||
- bin_sld_gsq
|
||||
- mul_sld
|
||||
- mul_sld_gs
|
||||
- mul_sld_gsq
|
||||
gs_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_gs
|
||||
- mul_sld
|
||||
- mul_sld_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
sld_vs_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_gs
|
||||
- mul_sld
|
||||
- mul_sld_gs
|
||||
- bin_pacc
|
||||
- bin_pacc_gs
|
||||
- mul_pacc
|
||||
- mul_pacc_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
pacc_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_pacc
|
||||
- bin_pacc_gs
|
||||
- mul_pacc
|
||||
- mul_pacc_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
|
||||
main_conf: &main_conf
|
||||
|
||||
global:
|
||||
METRICS:
|
||||
- acc
|
||||
- f1
|
||||
DATASET_N_PREVS: 9
|
||||
DATASET_DIR_UPDATE: true
|
||||
|
||||
confs:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: CCAT
|
||||
- DATASET_NAME: imdb
|
||||
confs_next:
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: GCAT
|
||||
- DATASET_NAME: rcv1
|
||||
DATASET_TARGET: MCAT
|
||||
|
||||
plot_confs:
|
||||
gs_vs_qgs:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_sld_gsq
|
||||
- bin_sld_gsq
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
PLOT_STDEV: true
|
||||
plot_confs_completed:
|
||||
max_conf_vs_atc_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_pacc
|
||||
- binmc_pacc
|
||||
- mul_pacc
|
||||
- mulmc_pacc
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
max_conf_vs_entropy_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- binmc_pacc
|
||||
- binne_pacc
|
||||
- mulmc_pacc
|
||||
- mulne_pacc
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
gs_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_pacc_gs
|
||||
- bin_pacc_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
PLOT_STDEV: true
|
||||
gs_vs_all:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_pacc_gs
|
||||
- bin_pacc_gs
|
||||
- atc_mc
|
||||
- doc_feat
|
||||
- kfcv
|
||||
PLOT_STDEV: true
|
||||
gs_vs_qgs:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_gs
|
||||
- bin_sld_gs
|
||||
- mul_sld_gsq
|
||||
- bin_sld_gsq
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
PLOT_STDEV: true
|
||||
cc_vs_other:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_cc
|
||||
- bin_cc
|
||||
- mul_sld
|
||||
- bin_sld
|
||||
- mul_pacc
|
||||
- bin_pacc
|
||||
PLOT_STDEV: true
|
||||
max_conf_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- binmc_sld
|
||||
- mul_sld
|
||||
- mulmc_sld
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
max_conf_vs_entropy:
|
||||
PLOT_ESTIMATORS:
|
||||
- binmc_sld
|
||||
- binne_sld
|
||||
- mulmc_sld
|
||||
- mulne_sld
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
sld_vs_pacc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- mul_sld
|
||||
- bin_pacc
|
||||
- mul_pacc
|
||||
- atc_mc
|
||||
PLOT_STDEV: true
|
||||
plot_confs_other:
|
||||
best_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- mul_sld_bcts
|
||||
- mul_sld_gs
|
||||
- bin_sld_bcts
|
||||
- bin_sld_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
all_vs_atc:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld
|
||||
- bin_sld_bcts
|
||||
- bin_sld_gs
|
||||
- mul_sld
|
||||
- mul_sld_bcts
|
||||
- mul_sld_gs
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
best_vs_all:
|
||||
PLOT_ESTIMATORS:
|
||||
- bin_sld_bcts
|
||||
- bin_sld_gs
|
||||
- mul_sld_bcts
|
||||
- mul_sld_gs
|
||||
- kfcv
|
||||
- atc_mc
|
||||
- atc_ne
|
||||
- doc_feat
|
||||
|
||||
exec: *main_conf
|
||||
890
out_imdb.md
890
out_imdb.md
|
|
@ -1,445 +1,445 @@
|
|||
|
||||
<div>target: default</div>
|
||||
<div>train: [0.5 0.5]</div>
|
||||
<div>validation: [0.5 0.5]</div>
|
||||
<div>evaluate_binary: 277.300s</div>
|
||||
<div>evaluate_multiclass: 139.986s</div>
|
||||
<div>kfcv: 98.625s</div>
|
||||
<div>atc_mc: 93.304s</div>
|
||||
<div>atc_ne: 91.201s</div>
|
||||
<div>doc_feat: 29.930s</div>
|
||||
<div>rca_score: 1018.341s</div>
|
||||
<div>rca_star_score: 1013.733s</div>
|
||||
<div>tot: 1054.413s</div>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
<th>doc_feat</th>
|
||||
<th>rca</th>
|
||||
<th>rca_star</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0154</td>
|
||||
<td>0.0177</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0291</td>
|
||||
<td>0.0291</td>
|
||||
<td>0.0248</td>
|
||||
<td>0.2705</td>
|
||||
<td>0.2413</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0309</td>
|
||||
<td>0.0284</td>
|
||||
<td>0.0252</td>
|
||||
<td>0.0300</td>
|
||||
<td>0.0300</td>
|
||||
<td>0.0247</td>
|
||||
<td>0.2796</td>
|
||||
<td>0.2504</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0309</td>
|
||||
<td>0.0302</td>
|
||||
<td>0.0251</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0250</td>
|
||||
<td>0.2722</td>
|
||||
<td>0.2430</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0310</td>
|
||||
<td>0.0339</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.2684</td>
|
||||
<td>0.2392</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0411</td>
|
||||
<td>0.0407</td>
|
||||
<td>0.0259</td>
|
||||
<td>0.0292</td>
|
||||
<td>0.0292</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.2724</td>
|
||||
<td>0.2432</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0381</td>
|
||||
<td>0.0376</td>
|
||||
<td>0.0262</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0259</td>
|
||||
<td>0.2701</td>
|
||||
<td>0.2409</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0442</td>
|
||||
<td>0.0452</td>
|
||||
<td>0.0254</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0256</td>
|
||||
<td>0.2650</td>
|
||||
<td>0.2358</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0480</td>
|
||||
<td>0.0498</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0235</td>
|
||||
<td>0.2640</td>
|
||||
<td>0.2347</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0401</td>
|
||||
<td>0.0431</td>
|
||||
<td>0.0222</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0220</td>
|
||||
<td>0.2654</td>
|
||||
<td>0.2361</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0551</td>
|
||||
<td>0.0558</td>
|
||||
<td>0.0243</td>
|
||||
<td>0.0295</td>
|
||||
<td>0.0295</td>
|
||||
<td>0.0246</td>
|
||||
<td>0.1838</td>
|
||||
<td>0.1551</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0499</td>
|
||||
<td>0.0513</td>
|
||||
<td>0.0308</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0309</td>
|
||||
<td>0.1472</td>
|
||||
<td>0.1202</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0538</td>
|
||||
<td>0.0542</td>
|
||||
<td>0.0278</td>
|
||||
<td>0.0329</td>
|
||||
<td>0.0329</td>
|
||||
<td>0.0280</td>
|
||||
<td>0.1717</td>
|
||||
<td>0.1459</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0476</td>
|
||||
<td>0.0484</td>
|
||||
<td>0.0258</td>
|
||||
<td>0.0298</td>
|
||||
<td>0.0298</td>
|
||||
<td>0.0259</td>
|
||||
<td>0.2434</td>
|
||||
<td>0.2147</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0447</td>
|
||||
<td>0.0474</td>
|
||||
<td>0.0287</td>
|
||||
<td>0.0332</td>
|
||||
<td>0.0332</td>
|
||||
<td>0.0288</td>
|
||||
<td>0.2632</td>
|
||||
<td>0.2340</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0388</td>
|
||||
<td>0.0397</td>
|
||||
<td>0.0295</td>
|
||||
<td>0.0328</td>
|
||||
<td>0.0328</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.2659</td>
|
||||
<td>0.2367</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0336</td>
|
||||
<td>0.0399</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0293</td>
|
||||
<td>0.0293</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.2612</td>
|
||||
<td>0.2320</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0407</td>
|
||||
<td>0.0447</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0303</td>
|
||||
<td>0.0303</td>
|
||||
<td>0.0271</td>
|
||||
<td>0.2601</td>
|
||||
<td>0.2309</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.0383</td>
|
||||
<td>0.0423</td>
|
||||
<td>0.0219</td>
|
||||
<td>0.0278</td>
|
||||
<td>0.0278</td>
|
||||
<td>0.0220</td>
|
||||
<td>0.2670</td>
|
||||
<td>0.2378</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.0351</td>
|
||||
<td>0.0387</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.0275</td>
|
||||
<td>0.0275</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.2618</td>
|
||||
<td>0.2326</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.0238</td>
|
||||
<td>0.0263</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0272</td>
|
||||
<td>0.2602</td>
|
||||
<td>0.2310</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.0118</td>
|
||||
<td>0.0202</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.2571</td>
|
||||
<td>0.2279</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0088</td>
|
||||
<td>0.0100</td>
|
||||
<td>0.0580</td>
|
||||
<td>0.0183</td>
|
||||
<td>0.0183</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0175</td>
|
||||
<td>0.0159</td>
|
||||
<td>0.0605</td>
|
||||
<td>0.0193</td>
|
||||
<td>0.0193</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0184</td>
|
||||
<td>0.0176</td>
|
||||
<td>0.0532</td>
|
||||
<td>0.0189</td>
|
||||
<td>0.0189</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0188</td>
|
||||
<td>0.0204</td>
|
||||
<td>0.0475</td>
|
||||
<td>0.0180</td>
|
||||
<td>0.0180</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0269</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0455</td>
|
||||
<td>0.0206</td>
|
||||
<td>0.0206</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0265</td>
|
||||
<td>0.0261</td>
|
||||
<td>0.0401</td>
|
||||
<td>0.0242</td>
|
||||
<td>0.0242</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0328</td>
|
||||
<td>0.0336</td>
|
||||
<td>0.0331</td>
|
||||
<td>0.0208</td>
|
||||
<td>0.0208</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0386</td>
|
||||
<td>0.0394</td>
|
||||
<td>0.0307</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0211</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0343</td>
|
||||
<td>0.0371</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0265</td>
|
||||
<td>0.0265</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0511</td>
|
||||
<td>0.0512</td>
|
||||
<td>0.0231</td>
|
||||
<td>0.0275</td>
|
||||
<td>0.0275</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0517</td>
|
||||
<td>0.0529</td>
|
||||
<td>0.0306</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0319</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0584</td>
|
||||
<td>0.0583</td>
|
||||
<td>0.0308</td>
|
||||
<td>0.0354</td>
|
||||
<td>0.0354</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0590</td>
|
||||
<td>0.0599</td>
|
||||
<td>0.0363</td>
|
||||
<td>0.0357</td>
|
||||
<td>0.0357</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0635</td>
|
||||
<td>0.0662</td>
|
||||
<td>0.0506</td>
|
||||
<td>0.0440</td>
|
||||
<td>0.0440</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0596</td>
|
||||
<td>0.0638</td>
|
||||
<td>0.0654</td>
|
||||
<td>0.0457</td>
|
||||
<td>0.0457</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0627</td>
|
||||
<td>0.0744</td>
|
||||
<td>0.0964</td>
|
||||
<td>0.0461</td>
|
||||
<td>0.0461</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0909</td>
|
||||
<td>0.0999</td>
|
||||
<td>0.1400</td>
|
||||
<td>0.0629</td>
|
||||
<td>0.0629</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.1052</td>
|
||||
<td>0.1126</td>
|
||||
<td>0.1829</td>
|
||||
<td>0.0727</td>
|
||||
<td>0.0727</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.1377</td>
|
||||
<td>0.1481</td>
|
||||
<td>0.2839</td>
|
||||
<td>0.1215</td>
|
||||
<td>0.1215</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.1305</td>
|
||||
<td>0.1450</td>
|
||||
<td>0.4592</td>
|
||||
<td>0.2037</td>
|
||||
<td>0.2037</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.1092</td>
|
||||
<td>0.1387</td>
|
||||
<td>0.8818</td>
|
||||
<td>0.5267</td>
|
||||
<td>0.5267</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<div>target: default</div>
|
||||
<div>train: [0.5 0.5]</div>
|
||||
<div>validation: [0.5 0.5]</div>
|
||||
<div>evaluate_binary: 277.300s</div>
|
||||
<div>evaluate_multiclass: 139.986s</div>
|
||||
<div>kfcv: 98.625s</div>
|
||||
<div>atc_mc: 93.304s</div>
|
||||
<div>atc_ne: 91.201s</div>
|
||||
<div>doc_feat: 29.930s</div>
|
||||
<div>rca_score: 1018.341s</div>
|
||||
<div>rca_star_score: 1013.733s</div>
|
||||
<div>tot: 1054.413s</div>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
<th>doc_feat</th>
|
||||
<th>rca</th>
|
||||
<th>rca_star</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0154</td>
|
||||
<td>0.0177</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0291</td>
|
||||
<td>0.0291</td>
|
||||
<td>0.0248</td>
|
||||
<td>0.2705</td>
|
||||
<td>0.2413</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0309</td>
|
||||
<td>0.0284</td>
|
||||
<td>0.0252</td>
|
||||
<td>0.0300</td>
|
||||
<td>0.0300</td>
|
||||
<td>0.0247</td>
|
||||
<td>0.2796</td>
|
||||
<td>0.2504</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0309</td>
|
||||
<td>0.0302</td>
|
||||
<td>0.0251</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0250</td>
|
||||
<td>0.2722</td>
|
||||
<td>0.2430</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0310</td>
|
||||
<td>0.0339</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.2684</td>
|
||||
<td>0.2392</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0411</td>
|
||||
<td>0.0407</td>
|
||||
<td>0.0259</td>
|
||||
<td>0.0292</td>
|
||||
<td>0.0292</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.2724</td>
|
||||
<td>0.2432</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0381</td>
|
||||
<td>0.0376</td>
|
||||
<td>0.0262</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0259</td>
|
||||
<td>0.2701</td>
|
||||
<td>0.2409</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0442</td>
|
||||
<td>0.0452</td>
|
||||
<td>0.0254</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0256</td>
|
||||
<td>0.2650</td>
|
||||
<td>0.2358</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0480</td>
|
||||
<td>0.0498</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0235</td>
|
||||
<td>0.2640</td>
|
||||
<td>0.2347</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0401</td>
|
||||
<td>0.0431</td>
|
||||
<td>0.0222</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0220</td>
|
||||
<td>0.2654</td>
|
||||
<td>0.2361</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0551</td>
|
||||
<td>0.0558</td>
|
||||
<td>0.0243</td>
|
||||
<td>0.0295</td>
|
||||
<td>0.0295</td>
|
||||
<td>0.0246</td>
|
||||
<td>0.1838</td>
|
||||
<td>0.1551</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0499</td>
|
||||
<td>0.0513</td>
|
||||
<td>0.0308</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0309</td>
|
||||
<td>0.1472</td>
|
||||
<td>0.1202</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0538</td>
|
||||
<td>0.0542</td>
|
||||
<td>0.0278</td>
|
||||
<td>0.0329</td>
|
||||
<td>0.0329</td>
|
||||
<td>0.0280</td>
|
||||
<td>0.1717</td>
|
||||
<td>0.1459</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0476</td>
|
||||
<td>0.0484</td>
|
||||
<td>0.0258</td>
|
||||
<td>0.0298</td>
|
||||
<td>0.0298</td>
|
||||
<td>0.0259</td>
|
||||
<td>0.2434</td>
|
||||
<td>0.2147</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0447</td>
|
||||
<td>0.0474</td>
|
||||
<td>0.0287</td>
|
||||
<td>0.0332</td>
|
||||
<td>0.0332</td>
|
||||
<td>0.0288</td>
|
||||
<td>0.2632</td>
|
||||
<td>0.2340</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0388</td>
|
||||
<td>0.0397</td>
|
||||
<td>0.0295</td>
|
||||
<td>0.0328</td>
|
||||
<td>0.0328</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.2659</td>
|
||||
<td>0.2367</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0336</td>
|
||||
<td>0.0399</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0293</td>
|
||||
<td>0.0293</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.2612</td>
|
||||
<td>0.2320</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0407</td>
|
||||
<td>0.0447</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0303</td>
|
||||
<td>0.0303</td>
|
||||
<td>0.0271</td>
|
||||
<td>0.2601</td>
|
||||
<td>0.2309</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.0383</td>
|
||||
<td>0.0423</td>
|
||||
<td>0.0219</td>
|
||||
<td>0.0278</td>
|
||||
<td>0.0278</td>
|
||||
<td>0.0220</td>
|
||||
<td>0.2670</td>
|
||||
<td>0.2378</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.0351</td>
|
||||
<td>0.0387</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.0275</td>
|
||||
<td>0.0275</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.2618</td>
|
||||
<td>0.2326</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.0238</td>
|
||||
<td>0.0263</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0296</td>
|
||||
<td>0.0272</td>
|
||||
<td>0.2602</td>
|
||||
<td>0.2310</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.0118</td>
|
||||
<td>0.0202</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0279</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.2571</td>
|
||||
<td>0.2279</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0088</td>
|
||||
<td>0.0100</td>
|
||||
<td>0.0580</td>
|
||||
<td>0.0183</td>
|
||||
<td>0.0183</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0175</td>
|
||||
<td>0.0159</td>
|
||||
<td>0.0605</td>
|
||||
<td>0.0193</td>
|
||||
<td>0.0193</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0184</td>
|
||||
<td>0.0176</td>
|
||||
<td>0.0532</td>
|
||||
<td>0.0189</td>
|
||||
<td>0.0189</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0188</td>
|
||||
<td>0.0204</td>
|
||||
<td>0.0475</td>
|
||||
<td>0.0180</td>
|
||||
<td>0.0180</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0269</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0455</td>
|
||||
<td>0.0206</td>
|
||||
<td>0.0206</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0265</td>
|
||||
<td>0.0261</td>
|
||||
<td>0.0401</td>
|
||||
<td>0.0242</td>
|
||||
<td>0.0242</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0328</td>
|
||||
<td>0.0336</td>
|
||||
<td>0.0331</td>
|
||||
<td>0.0208</td>
|
||||
<td>0.0208</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0386</td>
|
||||
<td>0.0394</td>
|
||||
<td>0.0307</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0211</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0343</td>
|
||||
<td>0.0371</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0265</td>
|
||||
<td>0.0265</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0511</td>
|
||||
<td>0.0512</td>
|
||||
<td>0.0231</td>
|
||||
<td>0.0275</td>
|
||||
<td>0.0275</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0517</td>
|
||||
<td>0.0529</td>
|
||||
<td>0.0306</td>
|
||||
<td>0.0319</td>
|
||||
<td>0.0319</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0584</td>
|
||||
<td>0.0583</td>
|
||||
<td>0.0308</td>
|
||||
<td>0.0354</td>
|
||||
<td>0.0354</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0590</td>
|
||||
<td>0.0599</td>
|
||||
<td>0.0363</td>
|
||||
<td>0.0357</td>
|
||||
<td>0.0357</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0635</td>
|
||||
<td>0.0662</td>
|
||||
<td>0.0506</td>
|
||||
<td>0.0440</td>
|
||||
<td>0.0440</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0596</td>
|
||||
<td>0.0638</td>
|
||||
<td>0.0654</td>
|
||||
<td>0.0457</td>
|
||||
<td>0.0457</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0627</td>
|
||||
<td>0.0744</td>
|
||||
<td>0.0964</td>
|
||||
<td>0.0461</td>
|
||||
<td>0.0461</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0909</td>
|
||||
<td>0.0999</td>
|
||||
<td>0.1400</td>
|
||||
<td>0.0629</td>
|
||||
<td>0.0629</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.1052</td>
|
||||
<td>0.1126</td>
|
||||
<td>0.1829</td>
|
||||
<td>0.0727</td>
|
||||
<td>0.0727</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.1377</td>
|
||||
<td>0.1481</td>
|
||||
<td>0.2839</td>
|
||||
<td>0.1215</td>
|
||||
<td>0.1215</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.1305</td>
|
||||
<td>0.1450</td>
|
||||
<td>0.4592</td>
|
||||
<td>0.2037</td>
|
||||
<td>0.2037</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.1092</td>
|
||||
<td>0.1387</td>
|
||||
<td>0.8818</td>
|
||||
<td>0.5267</td>
|
||||
<td>0.5267</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
|
|
|||
34710
out_rcv1.md
34710
out_rcv1.md
File diff suppressed because it is too large
Load Diff
890
out_spambase.md
890
out_spambase.md
|
|
@ -1,445 +1,445 @@
|
|||
|
||||
<div>target: default</div>
|
||||
<div>train: [0.60621118 0.39378882]</div>
|
||||
<div>validation: [0.60559006 0.39440994]</div>
|
||||
<div>evaluate_binary: 31.883s</div>
|
||||
<div>evaluate_multiclass: 24.748s</div>
|
||||
<div>kfcv: 23.957s</div>
|
||||
<div>atc_mc: 36.062s</div>
|
||||
<div>atc_ne: 37.123s</div>
|
||||
<div>doc_feat: 7.063s</div>
|
||||
<div>rca_score: 148.420s</div>
|
||||
<div>rca_star_score: 145.690s</div>
|
||||
<div>tot: 149.118s</div>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
<th>doc_feat</th>
|
||||
<th>rca</th>
|
||||
<th>rca_star</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0411</td>
|
||||
<td>0.0907</td>
|
||||
<td>0.0208</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0204</td>
|
||||
<td>0.1106</td>
|
||||
<td>0.1059</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0392</td>
|
||||
<td>0.0897</td>
|
||||
<td>0.0216</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0523</td>
|
||||
<td>0.0510</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0371</td>
|
||||
<td>0.0891</td>
|
||||
<td>0.0232</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0227</td>
|
||||
<td>0.0347</td>
|
||||
<td>0.0354</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0464</td>
|
||||
<td>0.0853</td>
|
||||
<td>0.0226</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0222</td>
|
||||
<td>0.0315</td>
|
||||
<td>0.0341</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0414</td>
|
||||
<td>0.0757</td>
|
||||
<td>0.0202</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0280</td>
|
||||
<td>0.0302</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0468</td>
|
||||
<td>0.0768</td>
|
||||
<td>0.0204</td>
|
||||
<td>0.0250</td>
|
||||
<td>0.0250</td>
|
||||
<td>0.0201</td>
|
||||
<td>0.0335</td>
|
||||
<td>0.0376</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0384</td>
|
||||
<td>0.0739</td>
|
||||
<td>0.0201</td>
|
||||
<td>0.0252</td>
|
||||
<td>0.0252</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0349</td>
|
||||
<td>0.0410</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0386</td>
|
||||
<td>0.0715</td>
|
||||
<td>0.0198</td>
|
||||
<td>0.0239</td>
|
||||
<td>0.0239</td>
|
||||
<td>0.0196</td>
|
||||
<td>0.0376</td>
|
||||
<td>0.0448</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0392</td>
|
||||
<td>0.0657</td>
|
||||
<td>0.0199</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0197</td>
|
||||
<td>0.0315</td>
|
||||
<td>0.0391</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0380</td>
|
||||
<td>0.0679</td>
|
||||
<td>0.0213</td>
|
||||
<td>0.0258</td>
|
||||
<td>0.0258</td>
|
||||
<td>0.0212</td>
|
||||
<td>0.0358</td>
|
||||
<td>0.0450</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0400</td>
|
||||
<td>0.0670</td>
|
||||
<td>0.0218</td>
|
||||
<td>0.0228</td>
|
||||
<td>0.0228</td>
|
||||
<td>0.0217</td>
|
||||
<td>0.0441</td>
|
||||
<td>0.0550</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0403</td>
|
||||
<td>0.0686</td>
|
||||
<td>0.0203</td>
|
||||
<td>0.0237</td>
|
||||
<td>0.0237</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0398</td>
|
||||
<td>0.0507</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0432</td>
|
||||
<td>0.0625</td>
|
||||
<td>0.0201</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0370</td>
|
||||
<td>0.0487</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0384</td>
|
||||
<td>0.0620</td>
|
||||
<td>0.0195</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0195</td>
|
||||
<td>0.0356</td>
|
||||
<td>0.0460</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0304</td>
|
||||
<td>0.0570</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0227</td>
|
||||
<td>0.0227</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0302</td>
|
||||
<td>0.0396</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0321</td>
|
||||
<td>0.0614</td>
|
||||
<td>0.0187</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0187</td>
|
||||
<td>0.0332</td>
|
||||
<td>0.0439</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0300</td>
|
||||
<td>0.0555</td>
|
||||
<td>0.0221</td>
|
||||
<td>0.0230</td>
|
||||
<td>0.0230</td>
|
||||
<td>0.0222</td>
|
||||
<td>0.0287</td>
|
||||
<td>0.0340</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.0325</td>
|
||||
<td>0.0540</td>
|
||||
<td>0.0224</td>
|
||||
<td>0.0229</td>
|
||||
<td>0.0229</td>
|
||||
<td>0.0225</td>
|
||||
<td>0.0342</td>
|
||||
<td>0.0360</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.0262</td>
|
||||
<td>0.0518</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0238</td>
|
||||
<td>0.0238</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0483</td>
|
||||
<td>0.0469</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.0243</td>
|
||||
<td>0.0576</td>
|
||||
<td>0.0197</td>
|
||||
<td>0.0240</td>
|
||||
<td>0.0240</td>
|
||||
<td>0.0196</td>
|
||||
<td>0.0806</td>
|
||||
<td>0.0746</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.0146</td>
|
||||
<td>0.0597</td>
|
||||
<td>0.0231</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.0232</td>
|
||||
<td>0.1600</td>
|
||||
<td>0.1515</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0239</td>
|
||||
<td>0.0477</td>
|
||||
<td>0.0345</td>
|
||||
<td>0.0162</td>
|
||||
<td>0.0162</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0235</td>
|
||||
<td>0.0496</td>
|
||||
<td>0.0320</td>
|
||||
<td>0.0169</td>
|
||||
<td>0.0169</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0230</td>
|
||||
<td>0.0520</td>
|
||||
<td>0.0289</td>
|
||||
<td>0.0171</td>
|
||||
<td>0.0171</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0308</td>
|
||||
<td>0.0528</td>
|
||||
<td>0.0274</td>
|
||||
<td>0.0171</td>
|
||||
<td>0.0171</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0286</td>
|
||||
<td>0.0490</td>
|
||||
<td>0.0291</td>
|
||||
<td>0.0186</td>
|
||||
<td>0.0186</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0346</td>
|
||||
<td>0.0534</td>
|
||||
<td>0.0255</td>
|
||||
<td>0.0186</td>
|
||||
<td>0.0186</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0299</td>
|
||||
<td>0.0545</td>
|
||||
<td>0.0232</td>
|
||||
<td>0.0205</td>
|
||||
<td>0.0205</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0335</td>
|
||||
<td>0.0566</td>
|
||||
<td>0.0217</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0211</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0360</td>
|
||||
<td>0.0562</td>
|
||||
<td>0.0217</td>
|
||||
<td>0.0226</td>
|
||||
<td>0.0226</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0372</td>
|
||||
<td>0.0626</td>
|
||||
<td>0.0213</td>
|
||||
<td>0.0246</td>
|
||||
<td>0.0246</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0437</td>
|
||||
<td>0.0677</td>
|
||||
<td>0.0223</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0241</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0486</td>
|
||||
<td>0.0762</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0269</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0572</td>
|
||||
<td>0.0779</td>
|
||||
<td>0.0290</td>
|
||||
<td>0.0312</td>
|
||||
<td>0.0312</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0580</td>
|
||||
<td>0.0866</td>
|
||||
<td>0.0340</td>
|
||||
<td>0.0341</td>
|
||||
<td>0.0341</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0546</td>
|
||||
<td>0.0919</td>
|
||||
<td>0.0420</td>
|
||||
<td>0.0374</td>
|
||||
<td>0.0374</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0636</td>
|
||||
<td>0.1161</td>
|
||||
<td>0.0689</td>
|
||||
<td>0.0533</td>
|
||||
<td>0.0533</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0750</td>
|
||||
<td>0.1192</td>
|
||||
<td>0.0768</td>
|
||||
<td>0.0560</td>
|
||||
<td>0.0560</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.1031</td>
|
||||
<td>0.1580</td>
|
||||
<td>0.1244</td>
|
||||
<td>0.0728</td>
|
||||
<td>0.0728</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.1175</td>
|
||||
<td>0.2412</td>
|
||||
<td>0.1885</td>
|
||||
<td>0.1100</td>
|
||||
<td>0.1100</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.1877</td>
|
||||
<td>0.3434</td>
|
||||
<td>0.3579</td>
|
||||
<td>0.2053</td>
|
||||
<td>0.2053</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.2717</td>
|
||||
<td>0.3136</td>
|
||||
<td>0.9178</td>
|
||||
<td>0.6264</td>
|
||||
<td>0.6264</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<div>target: default</div>
|
||||
<div>train: [0.60621118 0.39378882]</div>
|
||||
<div>validation: [0.60559006 0.39440994]</div>
|
||||
<div>evaluate_binary: 31.883s</div>
|
||||
<div>evaluate_multiclass: 24.748s</div>
|
||||
<div>kfcv: 23.957s</div>
|
||||
<div>atc_mc: 36.062s</div>
|
||||
<div>atc_ne: 37.123s</div>
|
||||
<div>doc_feat: 7.063s</div>
|
||||
<div>rca_score: 148.420s</div>
|
||||
<div>rca_star_score: 145.690s</div>
|
||||
<div>tot: 149.118s</div>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
<th>doc_feat</th>
|
||||
<th>rca</th>
|
||||
<th>rca_star</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0411</td>
|
||||
<td>0.0907</td>
|
||||
<td>0.0208</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0204</td>
|
||||
<td>0.1106</td>
|
||||
<td>0.1059</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0392</td>
|
||||
<td>0.0897</td>
|
||||
<td>0.0216</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0266</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0523</td>
|
||||
<td>0.0510</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0371</td>
|
||||
<td>0.0891</td>
|
||||
<td>0.0232</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0267</td>
|
||||
<td>0.0227</td>
|
||||
<td>0.0347</td>
|
||||
<td>0.0354</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0464</td>
|
||||
<td>0.0853</td>
|
||||
<td>0.0226</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0257</td>
|
||||
<td>0.0222</td>
|
||||
<td>0.0315</td>
|
||||
<td>0.0341</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0414</td>
|
||||
<td>0.0757</td>
|
||||
<td>0.0202</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0280</td>
|
||||
<td>0.0302</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0468</td>
|
||||
<td>0.0768</td>
|
||||
<td>0.0204</td>
|
||||
<td>0.0250</td>
|
||||
<td>0.0250</td>
|
||||
<td>0.0201</td>
|
||||
<td>0.0335</td>
|
||||
<td>0.0376</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0384</td>
|
||||
<td>0.0739</td>
|
||||
<td>0.0201</td>
|
||||
<td>0.0252</td>
|
||||
<td>0.0252</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0349</td>
|
||||
<td>0.0410</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0386</td>
|
||||
<td>0.0715</td>
|
||||
<td>0.0198</td>
|
||||
<td>0.0239</td>
|
||||
<td>0.0239</td>
|
||||
<td>0.0196</td>
|
||||
<td>0.0376</td>
|
||||
<td>0.0448</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0392</td>
|
||||
<td>0.0657</td>
|
||||
<td>0.0199</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0249</td>
|
||||
<td>0.0197</td>
|
||||
<td>0.0315</td>
|
||||
<td>0.0391</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0380</td>
|
||||
<td>0.0679</td>
|
||||
<td>0.0213</td>
|
||||
<td>0.0258</td>
|
||||
<td>0.0258</td>
|
||||
<td>0.0212</td>
|
||||
<td>0.0358</td>
|
||||
<td>0.0450</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0400</td>
|
||||
<td>0.0670</td>
|
||||
<td>0.0218</td>
|
||||
<td>0.0228</td>
|
||||
<td>0.0228</td>
|
||||
<td>0.0217</td>
|
||||
<td>0.0441</td>
|
||||
<td>0.0550</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0403</td>
|
||||
<td>0.0686</td>
|
||||
<td>0.0203</td>
|
||||
<td>0.0237</td>
|
||||
<td>0.0237</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0398</td>
|
||||
<td>0.0507</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0432</td>
|
||||
<td>0.0625</td>
|
||||
<td>0.0201</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.0245</td>
|
||||
<td>0.0200</td>
|
||||
<td>0.0370</td>
|
||||
<td>0.0487</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0384</td>
|
||||
<td>0.0620</td>
|
||||
<td>0.0195</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0195</td>
|
||||
<td>0.0356</td>
|
||||
<td>0.0460</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0304</td>
|
||||
<td>0.0570</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0227</td>
|
||||
<td>0.0227</td>
|
||||
<td>0.0236</td>
|
||||
<td>0.0302</td>
|
||||
<td>0.0396</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0321</td>
|
||||
<td>0.0614</td>
|
||||
<td>0.0187</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0273</td>
|
||||
<td>0.0187</td>
|
||||
<td>0.0332</td>
|
||||
<td>0.0439</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0300</td>
|
||||
<td>0.0555</td>
|
||||
<td>0.0221</td>
|
||||
<td>0.0230</td>
|
||||
<td>0.0230</td>
|
||||
<td>0.0222</td>
|
||||
<td>0.0287</td>
|
||||
<td>0.0340</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.0325</td>
|
||||
<td>0.0540</td>
|
||||
<td>0.0224</td>
|
||||
<td>0.0229</td>
|
||||
<td>0.0229</td>
|
||||
<td>0.0225</td>
|
||||
<td>0.0342</td>
|
||||
<td>0.0360</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.0262</td>
|
||||
<td>0.0518</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0238</td>
|
||||
<td>0.0238</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0483</td>
|
||||
<td>0.0469</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.0243</td>
|
||||
<td>0.0576</td>
|
||||
<td>0.0197</td>
|
||||
<td>0.0240</td>
|
||||
<td>0.0240</td>
|
||||
<td>0.0196</td>
|
||||
<td>0.0806</td>
|
||||
<td>0.0746</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.0146</td>
|
||||
<td>0.0597</td>
|
||||
<td>0.0231</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.0244</td>
|
||||
<td>0.0232</td>
|
||||
<td>0.1600</td>
|
||||
<td>0.1515</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>bin</th>
|
||||
<th>mul</th>
|
||||
<th>kfcv</th>
|
||||
<th>atc_mc</th>
|
||||
<th>atc_ne</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>(0.0, 1.0)</th>
|
||||
<td>0.0239</td>
|
||||
<td>0.0477</td>
|
||||
<td>0.0345</td>
|
||||
<td>0.0162</td>
|
||||
<td>0.0162</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.05, 0.95)</th>
|
||||
<td>0.0235</td>
|
||||
<td>0.0496</td>
|
||||
<td>0.0320</td>
|
||||
<td>0.0169</td>
|
||||
<td>0.0169</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.1, 0.9)</th>
|
||||
<td>0.0230</td>
|
||||
<td>0.0520</td>
|
||||
<td>0.0289</td>
|
||||
<td>0.0171</td>
|
||||
<td>0.0171</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.15, 0.85)</th>
|
||||
<td>0.0308</td>
|
||||
<td>0.0528</td>
|
||||
<td>0.0274</td>
|
||||
<td>0.0171</td>
|
||||
<td>0.0171</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.2, 0.8)</th>
|
||||
<td>0.0286</td>
|
||||
<td>0.0490</td>
|
||||
<td>0.0291</td>
|
||||
<td>0.0186</td>
|
||||
<td>0.0186</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.25, 0.75)</th>
|
||||
<td>0.0346</td>
|
||||
<td>0.0534</td>
|
||||
<td>0.0255</td>
|
||||
<td>0.0186</td>
|
||||
<td>0.0186</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.3, 0.7)</th>
|
||||
<td>0.0299</td>
|
||||
<td>0.0545</td>
|
||||
<td>0.0232</td>
|
||||
<td>0.0205</td>
|
||||
<td>0.0205</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.35, 0.65)</th>
|
||||
<td>0.0335</td>
|
||||
<td>0.0566</td>
|
||||
<td>0.0217</td>
|
||||
<td>0.0211</td>
|
||||
<td>0.0211</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.4, 0.6)</th>
|
||||
<td>0.0360</td>
|
||||
<td>0.0562</td>
|
||||
<td>0.0217</td>
|
||||
<td>0.0226</td>
|
||||
<td>0.0226</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.45, 0.55)</th>
|
||||
<td>0.0372</td>
|
||||
<td>0.0626</td>
|
||||
<td>0.0213</td>
|
||||
<td>0.0246</td>
|
||||
<td>0.0246</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.5, 0.5)</th>
|
||||
<td>0.0437</td>
|
||||
<td>0.0677</td>
|
||||
<td>0.0223</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0241</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.55, 0.45)</th>
|
||||
<td>0.0486</td>
|
||||
<td>0.0762</td>
|
||||
<td>0.0241</td>
|
||||
<td>0.0269</td>
|
||||
<td>0.0269</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.6, 0.4)</th>
|
||||
<td>0.0572</td>
|
||||
<td>0.0779</td>
|
||||
<td>0.0290</td>
|
||||
<td>0.0312</td>
|
||||
<td>0.0312</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.65, 0.35)</th>
|
||||
<td>0.0580</td>
|
||||
<td>0.0866</td>
|
||||
<td>0.0340</td>
|
||||
<td>0.0341</td>
|
||||
<td>0.0341</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.7, 0.3)</th>
|
||||
<td>0.0546</td>
|
||||
<td>0.0919</td>
|
||||
<td>0.0420</td>
|
||||
<td>0.0374</td>
|
||||
<td>0.0374</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.75, 0.25)</th>
|
||||
<td>0.0636</td>
|
||||
<td>0.1161</td>
|
||||
<td>0.0689</td>
|
||||
<td>0.0533</td>
|
||||
<td>0.0533</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.8, 0.2)</th>
|
||||
<td>0.0750</td>
|
||||
<td>0.1192</td>
|
||||
<td>0.0768</td>
|
||||
<td>0.0560</td>
|
||||
<td>0.0560</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.85, 0.15)</th>
|
||||
<td>0.1031</td>
|
||||
<td>0.1580</td>
|
||||
<td>0.1244</td>
|
||||
<td>0.0728</td>
|
||||
<td>0.0728</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.9, 0.1)</th>
|
||||
<td>0.1175</td>
|
||||
<td>0.2412</td>
|
||||
<td>0.1885</td>
|
||||
<td>0.1100</td>
|
||||
<td>0.1100</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(0.95, 0.05)</th>
|
||||
<td>0.1877</td>
|
||||
<td>0.3434</td>
|
||||
<td>0.3579</td>
|
||||
<td>0.2053</td>
|
||||
<td>0.2053</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>(1.0, 0.0)</th>
|
||||
<td>0.2717</td>
|
||||
<td>0.3136</td>
|
||||
<td>0.9178</td>
|
||||
<td>0.6264</td>
|
||||
<td>0.6264</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
|
|
|||
|
|
@ -1,447 +1,447 @@
|
|||
06/11/23 05:49:49| INFO dataset imdb_9prevs
|
||||
06/11/23 05:49:57| INFO Dataset sample 0.10 of dataset imdb_9prevs started
|
||||
06/11/23 05:50:12| INFO ref finished [took 13.3064s]
|
||||
06/11/23 05:50:17| INFO atc_mc finished [took 17.3508s]
|
||||
06/11/23 05:50:19| INFO mul_pacc finished [took 20.0802s]
|
||||
06/11/23 05:50:22| INFO mulne_sld finished [took 23.6723s]
|
||||
06/11/23 05:50:24| INFO mulmc_sld finished [took 25.5159s]
|
||||
06/11/23 05:50:39| INFO mul_sld finished [took 40.7099s]
|
||||
06/11/23 05:52:55| INFO bin_pacc finished [took 176.3728s]
|
||||
06/11/23 05:53:05| INFO binmc_sld finished [took 186.8240s]
|
||||
06/11/23 05:53:06| INFO binne_sld finished [took 187.6585s]
|
||||
06/11/23 05:53:07| INFO bin_sld finished [took 189.1728s]
|
||||
06/11/23 05:53:07| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 189.6034s]
|
||||
06/11/23 05:53:07| INFO Dataset sample 0.20 of dataset imdb_9prevs started
|
||||
06/11/23 05:53:22| INFO ref finished [took 13.2778s]
|
||||
06/11/23 05:53:26| INFO atc_mc finished [took 17.4491s]
|
||||
06/11/23 05:53:28| INFO mul_pacc finished [took 19.9359s]
|
||||
06/11/23 05:53:40| INFO mulmc_sld finished [took 31.6686s]
|
||||
06/11/23 05:53:44| INFO mulne_sld finished [took 35.2085s]
|
||||
06/11/23 05:53:44| INFO mul_sld finished [took 36.2502s]
|
||||
06/11/23 05:56:05| INFO bin_pacc finished [took 177.0225s]
|
||||
06/11/23 05:56:13| INFO binmc_sld finished [took 185.4811s]
|
||||
06/11/23 05:56:15| INFO bin_sld finished [took 187.1039s]
|
||||
06/11/23 05:56:16| INFO binne_sld finished [took 187.3163s]
|
||||
06/11/23 05:56:16| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 188.4781s]
|
||||
06/11/23 05:56:16| INFO Dataset sample 0.30 of dataset imdb_9prevs started
|
||||
06/11/23 05:56:31| INFO ref finished [took 13.4513s]
|
||||
06/11/23 05:56:36| INFO atc_mc finished [took 18.1025s]
|
||||
06/11/23 05:56:38| INFO mul_pacc finished [took 20.3997s]
|
||||
06/11/23 05:56:45| INFO mulmc_sld finished [took 28.4298s]
|
||||
06/11/23 05:56:46| INFO mulne_sld finished [took 28.8678s]
|
||||
06/11/23 05:56:46| INFO mul_sld finished [took 29.5573s]
|
||||
06/11/23 05:59:11| INFO bin_pacc finished [took 174.0262s]
|
||||
06/11/23 05:59:17| INFO binmc_sld finished [took 180.1998s]
|
||||
06/11/23 05:59:18| INFO binne_sld finished [took 181.2200s]
|
||||
06/11/23 05:59:19| INFO bin_sld finished [took 182.1672s]
|
||||
06/11/23 05:59:19| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 183.0515s]
|
||||
06/11/23 05:59:19| INFO Dataset sample 0.40 of dataset imdb_9prevs started
|
||||
06/11/23 05:59:34| INFO ref finished [took 13.5163s]
|
||||
06/11/23 05:59:39| INFO atc_mc finished [took 17.9856s]
|
||||
06/11/23 05:59:41| INFO mul_pacc finished [took 20.7441s]
|
||||
06/11/23 05:59:49| INFO mulmc_sld finished [took 29.2747s]
|
||||
06/11/23 05:59:50| INFO mulne_sld finished [took 29.6624s]
|
||||
06/11/23 05:59:50| INFO mul_sld finished [took 30.3432s]
|
||||
06/11/23 06:02:17| INFO bin_pacc finished [took 176.7354s]
|
||||
06/11/23 06:02:19| INFO binmc_sld finished [took 179.9981s]
|
||||
06/11/23 06:02:21| INFO bin_sld finished [took 181.6844s]
|
||||
06/11/23 06:02:22| INFO binne_sld finished [took 182.0846s]
|
||||
06/11/23 06:02:22| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 183.2033s]
|
||||
06/11/23 06:02:22| INFO Dataset sample 0.50 of dataset imdb_9prevs started
|
||||
06/11/23 06:02:37| INFO ref finished [took 13.4688s]
|
||||
06/11/23 06:02:42| INFO atc_mc finished [took 18.0218s]
|
||||
06/11/23 06:02:44| INFO mul_pacc finished [took 20.5800s]
|
||||
06/11/23 06:02:52| INFO mulmc_sld finished [took 29.0192s]
|
||||
06/11/23 06:02:52| INFO mul_sld finished [took 29.4403s]
|
||||
06/11/23 06:02:52| INFO mulne_sld finished [took 29.1611s]
|
||||
06/11/23 06:05:19| INFO bin_pacc finished [took 175.5125s]
|
||||
06/11/23 06:05:23| INFO binmc_sld finished [took 180.0427s]
|
||||
06/11/23 06:05:25| INFO binne_sld finished [took 182.5814s]
|
||||
06/11/23 06:05:26| INFO bin_sld finished [took 183.2892s]
|
||||
06/11/23 06:05:26| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 183.8611s]
|
||||
06/11/23 06:05:26| INFO Dataset sample 0.60 of dataset imdb_9prevs started
|
||||
06/11/23 06:05:41| INFO ref finished [took 13.4643s]
|
||||
06/11/23 06:05:45| INFO atc_mc finished [took 17.9768s]
|
||||
06/11/23 06:05:48| INFO mul_pacc finished [took 20.7525s]
|
||||
06/11/23 06:05:55| INFO mulmc_sld finished [took 28.8234s]
|
||||
06/11/23 06:05:55| INFO mulne_sld finished [took 28.6537s]
|
||||
06/11/23 06:05:56| INFO mul_sld finished [took 29.6167s]
|
||||
06/11/23 06:08:24| INFO bin_pacc finished [took 176.5335s]
|
||||
06/11/23 06:08:27| INFO binmc_sld finished [took 180.4803s]
|
||||
06/11/23 06:08:28| INFO bin_sld finished [took 181.6676s]
|
||||
06/11/23 06:08:29| INFO binne_sld finished [took 182.0534s]
|
||||
06/11/23 06:08:29| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 183.0240s]
|
||||
06/11/23 06:08:29| INFO Dataset sample 0.70 of dataset imdb_9prevs started
|
||||
06/11/23 06:08:44| INFO ref finished [took 13.7566s]
|
||||
06/11/23 06:08:49| INFO atc_mc finished [took 17.9495s]
|
||||
06/11/23 06:08:51| INFO mul_pacc finished [took 20.5859s]
|
||||
06/11/23 06:08:57| INFO mulmc_sld finished [took 27.4370s]
|
||||
06/11/23 06:08:58| INFO mul_sld finished [took 28.3224s]
|
||||
06/11/23 06:08:58| INFO mulne_sld finished [took 28.1390s]
|
||||
06/11/23 06:11:26| INFO bin_pacc finished [took 175.7412s]
|
||||
06/11/23 06:11:31| INFO binmc_sld finished [took 181.4310s]
|
||||
06/11/23 06:11:32| INFO binne_sld finished [took 182.0095s]
|
||||
06/11/23 06:11:33| INFO bin_sld finished [took 183.6520s]
|
||||
06/11/23 06:11:33| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 184.2005s]
|
||||
06/11/23 06:11:33| INFO Dataset sample 0.80 of dataset imdb_9prevs started
|
||||
06/11/23 06:11:48| INFO ref finished [took 13.5418s]
|
||||
06/11/23 06:11:53| INFO atc_mc finished [took 17.8150s]
|
||||
06/11/23 06:11:55| INFO mul_pacc finished [took 20.4761s]
|
||||
06/11/23 06:12:01| INFO mulmc_sld finished [took 27.2741s]
|
||||
06/11/23 06:12:02| INFO mulne_sld finished [took 27.2693s]
|
||||
06/11/23 06:12:02| INFO mul_sld finished [took 28.3364s]
|
||||
06/11/23 06:14:30| INFO bin_pacc finished [took 175.7637s]
|
||||
06/11/23 06:14:37| INFO binmc_sld finished [took 183.2422s]
|
||||
06/11/23 06:14:38| INFO bin_sld finished [took 184.1064s]
|
||||
06/11/23 06:14:39| INFO binne_sld finished [took 184.9073s]
|
||||
06/11/23 06:14:39| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 186.2580s]
|
||||
06/11/23 06:14:39| INFO Dataset sample 0.90 of dataset imdb_9prevs started
|
||||
06/11/23 06:14:41| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:14:41| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:14:52| INFO ref finished [took 11.6315s]
|
||||
06/11/23 06:14:56| INFO atc_mc finished [took 15.3068s]
|
||||
06/11/23 06:15:01| INFO mulne_sld finished [took 21.1133s]
|
||||
06/11/23 06:15:02| INFO mulmc_sld finished [took 22.2375s]
|
||||
06/11/23 06:15:08| INFO mul_sld finished [took 27.8149s]
|
||||
06/11/23 06:17:32| INFO binne_sld finished [took 171.8722s]
|
||||
06/11/23 06:17:32| INFO bin_sld finished [took 172.4710s]
|
||||
06/11/23 06:17:33| INFO binmc_sld finished [took 172.8193s]
|
||||
06/11/23 06:17:33| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 173.4411s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 14:48:04| INFO dataset imdb_9prevs
|
||||
06/11/23 14:48:14| INFO Dataset sample 0.10 of dataset imdb_9prevs started
|
||||
06/11/23 14:48:17| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 14:48:18| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 14:48:31| INFO doc_feat finished [took 11.5257s]
|
||||
06/11/23 14:48:36| INFO ref finished [took 18.5620s]
|
||||
06/11/23 14:48:42| INFO kfcv finished [took 24.7227s]
|
||||
06/11/23 14:48:44| INFO atc_ne finished [took 25.5676s]
|
||||
06/11/23 14:48:46| INFO atc_mc finished [took 27.4910s]
|
||||
06/11/23 14:48:50| INFO mulne_pacc finished [took 34.0415s]
|
||||
06/11/23 14:48:57| INFO mulmc_pacc finished [took 41.7500s]
|
||||
06/11/23 14:48:58| INFO mul_pacc finished [took 43.0162s]
|
||||
06/11/23 14:48:58| INFO mul_cc finished [took 40.3279s]
|
||||
06/11/23 14:49:16| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 14:49:26| INFO mul_sld finished [took 71.4588s]
|
||||
06/11/23 14:50:10| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 14:52:12| INFO binne_pacc finished [took 236.2174s]
|
||||
06/11/23 14:52:16| INFO binmc_pacc finished [took 240.4686s]
|
||||
06/11/23 14:52:19| INFO bin_cc finished [took 241.9141s]
|
||||
06/11/23 14:52:20| INFO bin_pacc finished [took 244.5632s]
|
||||
06/11/23 14:52:23| INFO bin_sld finished [took 249.0477s]
|
||||
06/11/23 14:53:48| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 14:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 443.6010s]
|
||||
06/11/23 14:55:51| INFO mul_sld_gs finished [took 455.9932s]
|
||||
06/11/23 14:55:51| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 456.7746s]
|
||||
06/11/23 14:55:51| INFO Dataset sample 0.20 of dataset imdb_9prevs started
|
||||
06/11/23 14:56:07| INFO doc_feat finished [took 11.2758s]
|
||||
06/11/23 14:56:18| INFO atc_mc finished [took 22.2986s]
|
||||
06/11/23 14:56:22| INFO ref finished [took 26.3482s]
|
||||
06/11/23 14:56:25| INFO kfcv finished [took 30.4761s]
|
||||
06/11/23 14:56:29| INFO mul_pacc finished [took 36.5892s]
|
||||
06/11/23 14:56:29| INFO mulmc_pacc finished [took 36.7773s]
|
||||
06/11/23 14:56:38| INFO atc_ne finished [took 41.7824s]
|
||||
06/11/23 14:56:41| INFO mulne_pacc finished [took 47.8318s]
|
||||
06/11/23 14:56:41| INFO mul_cc finished [took 46.7221s]
|
||||
06/11/23 14:56:55| INFO mul_sld finished [took 63.3547s]
|
||||
06/11/23 14:57:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.01017) [took 119.9166s]
|
||||
06/11/23 14:58:15| INFO mul_pacc_gs finished [took 141.4446s]
|
||||
06/11/23 15:00:38| INFO binne_pacc finished [took 285.5562s]
|
||||
06/11/23 15:00:48| INFO bin_cc finished [took 293.8727s]
|
||||
06/11/23 15:00:49| INFO binmc_pacc finished [took 296.7176s]
|
||||
06/11/23 15:00:49| INFO bin_pacc finished [took 297.1868s]
|
||||
06/11/23 15:01:03| INFO bin_sld finished [took 312.0358s]
|
||||
06/11/23 15:02:29| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:02:34| INFO bin_sld_gsq finished [took 402.0748s]
|
||||
06/11/23 15:03:56| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00980) [took 482.9237s]
|
||||
06/11/23 15:05:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 548.0443s]
|
||||
06/11/23 15:05:14| INFO mul_sld_gs finished [took 562.2966s]
|
||||
06/11/23 15:06:30| INFO bin_pacc_gs finished [took 636.7956s]
|
||||
06/11/23 15:10:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 884.9748s]
|
||||
06/11/23 15:13:11| INFO bin_sld_gs finished [took 1039.3282s]
|
||||
06/11/23 15:13:11| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 1040.0772s]
|
||||
06/11/23 15:13:11| INFO Dataset sample 0.30 of dataset imdb_9prevs started
|
||||
06/11/23 15:13:39| INFO doc_feat finished [took 22.8145s]
|
||||
06/11/23 15:13:41| INFO atc_ne finished [took 24.3471s]
|
||||
06/11/23 15:13:45| INFO ref finished [took 28.7559s]
|
||||
06/11/23 15:13:52| INFO mulne_pacc finished [took 38.1365s]
|
||||
06/11/23 15:13:53| INFO kfcv finished [took 37.4026s]
|
||||
06/11/23 15:13:56| INFO atc_mc finished [took 39.4198s]
|
||||
06/11/23 15:13:59| INFO mul_pacc finished [took 45.9542s]
|
||||
06/11/23 15:13:59| INFO mul_cc finished [took 43.9076s]
|
||||
06/11/23 15:13:59| INFO mulmc_pacc finished [took 45.9395s]
|
||||
06/11/23 15:14:11| INFO mul_sld finished [took 59.8835s]
|
||||
06/11/23 15:15:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01028) [took 128.2866s]
|
||||
06/11/23 15:15:44| INFO mul_pacc_gs finished [took 149.5820s]
|
||||
06/11/23 15:18:03| INFO binne_pacc finished [took 289.3504s]
|
||||
06/11/23 15:18:07| INFO bin_pacc finished [took 294.7115s]
|
||||
06/11/23 15:18:14| INFO bin_cc finished [took 298.6839s]
|
||||
06/11/23 15:18:14| INFO binmc_pacc finished [took 300.9499s]
|
||||
06/11/23 15:18:14| INFO bin_sld finished [took 302.9035s]
|
||||
06/11/23 15:19:46| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:20:05| INFO bin_sld_gsq finished [took 413.1151s]
|
||||
06/11/23 15:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00916) [took 488.7327s]
|
||||
06/11/23 15:22:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 541.2865s]
|
||||
06/11/23 15:22:28| INFO mul_sld_gs finished [took 556.0867s]
|
||||
06/11/23 15:23:57| INFO bin_pacc_gs finished [took 643.0717s]
|
||||
06/11/23 15:27:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 860.3135s]
|
||||
06/11/23 15:30:05| INFO bin_sld_gs finished [took 1013.1878s]
|
||||
06/11/23 15:30:05| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 1014.3141s]
|
||||
06/11/23 15:30:05| INFO Dataset sample 0.40 of dataset imdb_9prevs started
|
||||
06/11/23 15:30:24| INFO doc_feat finished [took 13.8500s]
|
||||
06/11/23 15:30:32| INFO ref finished [took 22.3531s]
|
||||
06/11/23 15:30:41| INFO mul_pacc finished [took 34.1860s]
|
||||
06/11/23 15:30:45| INFO atc_ne finished [took 34.8111s]
|
||||
06/11/23 15:30:46| INFO kfcv finished [took 36.4055s]
|
||||
06/11/23 15:30:49| INFO atc_mc finished [took 38.7978s]
|
||||
06/11/23 15:30:49| INFO mulmc_pacc finished [took 42.4552s]
|
||||
06/11/23 15:30:51| INFO mul_cc finished [took 42.6899s]
|
||||
06/11/23 15:30:53| INFO mulne_pacc finished [took 45.2694s]
|
||||
06/11/23 15:30:57| INFO mul_sld finished [took 51.2705s]
|
||||
06/11/23 15:32:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01220) [took 124.5801s]
|
||||
06/11/23 15:32:34| INFO mul_pacc_gs finished [took 145.3368s]
|
||||
06/11/23 15:34:56| INFO binmc_pacc finished [took 289.1451s]
|
||||
06/11/23 15:35:04| INFO bin_sld finished [took 298.3514s]
|
||||
06/11/23 15:35:04| INFO binne_pacc finished [took 296.5538s]
|
||||
06/11/23 15:35:05| INFO bin_pacc finished [took 298.5077s]
|
||||
06/11/23 15:35:09| INFO bin_cc finished [took 300.1332s]
|
||||
06/11/23 15:36:41| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:37:08| INFO bin_sld_gsq finished [took 421.3938s]
|
||||
06/11/23 15:38:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01137) [took 490.9644s]
|
||||
06/11/23 15:38:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 531.8225s]
|
||||
06/11/23 15:39:12| INFO mul_sld_gs finished [took 546.4524s]
|
||||
06/11/23 15:40:53| INFO bin_pacc_gs finished [took 645.0957s]
|
||||
06/11/23 15:44:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 882.0550s]
|
||||
06/11/23 15:47:19| INFO bin_sld_gs finished [took 1033.2802s]
|
||||
06/11/23 15:47:19| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 1034.1241s]
|
||||
06/11/23 15:47:19| INFO Dataset sample 0.50 of dataset imdb_9prevs started
|
||||
06/11/23 15:47:36| INFO doc_feat finished [took 11.6005s]
|
||||
06/11/23 15:47:40| INFO ref finished [took 16.3058s]
|
||||
06/11/23 15:47:50| INFO atc_mc finished [took 25.8745s]
|
||||
06/11/23 15:47:52| INFO kfcv finished [took 29.0931s]
|
||||
06/11/23 15:47:53| INFO atc_ne finished [took 28.8903s]
|
||||
06/11/23 15:47:53| INFO mul_pacc finished [took 32.5473s]
|
||||
06/11/23 15:48:00| INFO mul_cc finished [took 37.3478s]
|
||||
06/11/23 15:48:01| INFO mulne_pacc finished [took 39.9745s]
|
||||
06/11/23 15:48:02| INFO mulmc_pacc finished [took 40.5057s]
|
||||
06/11/23 15:48:10| INFO mul_sld finished [took 50.1825s]
|
||||
06/11/23 15:49:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01107) [took 125.0329s]
|
||||
06/11/23 15:49:49| INFO mul_pacc_gs finished [took 146.7316s]
|
||||
06/11/23 15:52:15| INFO bin_cc finished [took 292.6719s]
|
||||
06/11/23 15:52:15| INFO binne_pacc finished [took 293.9844s]
|
||||
06/11/23 15:52:17| INFO bin_pacc finished [took 296.2830s]
|
||||
06/11/23 15:52:21| INFO binmc_pacc finished [took 299.4873s]
|
||||
06/11/23 15:52:23| INFO bin_sld finished [took 303.4889s]
|
||||
06/11/23 15:53:57| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:54:18| INFO bin_sld_gsq finished [took 418.0959s]
|
||||
06/11/23 15:55:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 489.7797s]
|
||||
06/11/23 15:56:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 536.7408s]
|
||||
06/11/23 15:56:33| INFO mul_sld_gs finished [took 552.5393s]
|
||||
06/11/23 15:58:05| INFO bin_pacc_gs finished [took 643.1581s]
|
||||
06/11/23 16:01:42| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 862.6012s]
|
||||
06/11/23 16:04:15| INFO bin_sld_gs finished [took 1015.3606s]
|
||||
06/11/23 16:04:15| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 1016.0642s]
|
||||
06/11/23 16:04:15| INFO Dataset sample 0.60 of dataset imdb_9prevs started
|
||||
06/11/23 16:04:40| INFO doc_feat finished [took 19.9628s]
|
||||
06/11/23 16:04:41| INFO kfcv finished [took 21.8848s]
|
||||
06/11/23 16:04:46| INFO ref finished [took 26.2613s]
|
||||
06/11/23 16:04:56| INFO mulmc_pacc finished [took 38.6399s]
|
||||
06/11/23 16:04:56| INFO atc_ne finished [took 35.7501s]
|
||||
06/11/23 16:04:57| INFO atc_mc finished [took 37.3907s]
|
||||
06/11/23 16:05:01| INFO mul_cc finished [took 41.6420s]
|
||||
06/11/23 16:05:01| INFO mul_pacc finished [took 44.6898s]
|
||||
06/11/23 16:05:02| INFO mulne_pacc finished [took 44.7679s]
|
||||
06/11/23 16:05:12| INFO mul_sld finished [took 56.0834s]
|
||||
06/11/23 16:06:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01082) [took 125.2569s]
|
||||
06/11/23 16:06:44| INFO mul_pacc_gs finished [took 146.2318s]
|
||||
06/11/23 16:09:05| INFO binne_pacc finished [took 288.1949s]
|
||||
06/11/23 16:09:10| INFO bin_pacc finished [took 293.3207s]
|
||||
06/11/23 16:09:12| INFO bin_sld finished [took 296.1022s]
|
||||
06/11/23 16:09:13| INFO binmc_pacc finished [took 296.4000s]
|
||||
06/11/23 16:09:18| INFO bin_cc finished [took 299.1982s]
|
||||
06/11/23 16:10:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 16:11:22| INFO bin_sld_gsq finished [took 425.6641s]
|
||||
06/11/23 16:12:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00976) [took 492.8847s]
|
||||
06/11/23 16:13:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 536.8669s]
|
||||
06/11/23 16:13:28| INFO mul_sld_gs finished [took 551.6187s]
|
||||
06/11/23 16:15:03| INFO bin_pacc_gs finished [took 645.6602s]
|
||||
06/11/23 16:19:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 907.7074s]
|
||||
06/11/23 16:21:57| INFO bin_sld_gs finished [took 1060.9759s]
|
||||
06/11/23 16:21:57| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 1061.7730s]
|
||||
06/11/23 16:21:57| INFO Dataset sample 0.70 of dataset imdb_9prevs started
|
||||
06/11/23 16:22:23| INFO doc_feat finished [took 20.2428s]
|
||||
06/11/23 16:22:34| INFO kfcv finished [took 32.1532s]
|
||||
06/11/23 16:22:36| INFO ref finished [took 34.3738s]
|
||||
06/11/23 16:22:38| INFO mul_sld finished [took 40.1101s]
|
||||
06/11/23 16:22:40| INFO mul_cc finished [took 38.6722s]
|
||||
06/11/23 16:22:41| INFO atc_mc finished [took 38.9379s]
|
||||
06/11/23 16:22:43| INFO atc_ne finished [took 40.3132s]
|
||||
06/11/23 16:22:43| INFO mulne_pacc finished [took 43.7833s]
|
||||
06/11/23 16:22:44| INFO mulmc_pacc finished [took 44.4084s]
|
||||
06/11/23 16:22:46| INFO mul_pacc finished [took 47.7998s]
|
||||
06/11/23 16:24:08| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01575) [took 127.2393s]
|
||||
06/11/23 16:24:31| INFO mul_pacc_gs finished [took 150.2100s]
|
||||
06/11/23 16:26:49| INFO bin_cc finished [took 288.6128s]
|
||||
06/11/23 16:26:51| INFO bin_pacc finished [took 292.1757s]
|
||||
06/11/23 16:26:52| INFO binne_pacc finished [took 293.0194s]
|
||||
06/11/23 16:27:01| INFO binmc_pacc finished [took 302.5703s]
|
||||
06/11/23 16:27:01| INFO bin_sld finished [took 303.9303s]
|
||||
06/11/23 16:28:32| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 16:28:53| INFO bin_sld_gsq finished [took 414.4520s]
|
||||
06/11/23 16:30:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01641) [took 494.7681s]
|
||||
06/11/23 16:31:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 542.3282s]
|
||||
06/11/23 16:31:15| INFO mul_sld_gs finished [took 557.2859s]
|
||||
06/11/23 16:32:49| INFO bin_pacc_gs finished [took 648.9428s]
|
||||
06/11/23 16:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 864.7237s]
|
||||
06/11/23 16:38:54| INFO bin_sld_gs finished [took 1015.9618s]
|
||||
06/11/23 16:38:54| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 1016.7743s]
|
||||
06/11/23 16:38:54| INFO Dataset sample 0.80 of dataset imdb_9prevs started
|
||||
06/11/23 16:39:19| INFO doc_feat finished [took 19.9639s]
|
||||
06/11/23 16:39:22| INFO atc_mc finished [took 22.9650s]
|
||||
06/11/23 16:39:26| INFO kfcv finished [took 27.9671s]
|
||||
06/11/23 16:39:30| INFO mul_pacc finished [took 34.3899s]
|
||||
06/11/23 16:39:31| INFO ref finished [took 32.4692s]
|
||||
06/11/23 16:39:33| INFO mulne_pacc finished [took 37.2045s]
|
||||
06/11/23 16:39:39| INFO atc_ne finished [took 39.7686s]
|
||||
06/11/23 16:39:41| INFO mul_cc finished [took 42.9411s]
|
||||
06/11/23 16:39:41| INFO mulmc_pacc finished [took 44.9724s]
|
||||
06/11/23 16:39:46| INFO mul_sld finished [took 51.4269s]
|
||||
06/11/23 16:40:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01013) [took 122.2196s]
|
||||
06/11/23 16:41:24| INFO mul_pacc_gs finished [took 146.7076s]
|
||||
06/11/23 16:43:40| INFO binne_pacc finished [took 284.1154s]
|
||||
06/11/23 16:43:52| INFO bin_pacc finished [took 296.8885s]
|
||||
06/11/23 16:43:54| INFO bin_cc finished [took 297.1714s]
|
||||
06/11/23 16:43:56| INFO binmc_pacc finished [took 300.6806s]
|
||||
06/11/23 16:43:57| INFO bin_sld finished [took 302.6966s]
|
||||
06/11/23 16:45:26| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 16:45:41| INFO bin_sld_gsq finished [took 405.8247s]
|
||||
06/11/23 16:47:00| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00949) [took 483.3129s]
|
||||
06/11/23 16:47:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 539.6504s]
|
||||
06/11/23 16:48:09| INFO mul_sld_gs finished [took 553.8401s]
|
||||
06/11/23 16:49:34| INFO bin_pacc_gs finished [took 637.2772s]
|
||||
06/11/23 16:53:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 875.8870s]
|
||||
06/11/23 16:56:08| INFO bin_sld_gs finished [took 1033.4325s]
|
||||
06/11/23 16:56:08| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 1034.1983s]
|
||||
06/11/23 16:56:08| INFO Dataset sample 0.90 of dataset imdb_9prevs started
|
||||
06/11/23 16:56:09| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:09| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:11| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:11| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:22| INFO doc_feat finished [took 10.1613s]
|
||||
06/11/23 16:56:25| INFO ref finished [took 13.7569s]
|
||||
06/11/23 16:56:27| INFO kfcv finished [took 15.6337s]
|
||||
06/11/23 16:56:29| INFO atc_mc finished [took 18.0104s]
|
||||
06/11/23 16:56:30| INFO atc_ne finished [took 18.0260s]
|
||||
06/11/23 16:56:31| INFO mul_cc finished [took 20.6201s]
|
||||
06/11/23 16:56:40| INFO mul_sld finished [took 31.2942s]
|
||||
06/11/23 16:56:47| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 16:58:55| INFO bin_cc finished [took 164.5182s]
|
||||
06/11/23 16:58:59| INFO bin_sld finished [took 170.5046s]
|
||||
06/11/23 17:02:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 368.6067s]
|
||||
06/11/23 17:02:29| INFO mul_sld_gs finished [took 380.7801s]
|
||||
06/11/23 17:02:29| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 381.5305s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
07/11/23 03:31:29| INFO dataset imdb_9prevs
|
||||
07/11/23 03:31:37| INFO Dataset sample 0.10 of dataset imdb_9prevs started
|
||||
07/11/23 03:31:49| INFO ref finished [took 11.4117s]
|
||||
07/11/23 03:31:53| INFO atc_mc finished [took 14.8218s]
|
||||
07/11/23 03:31:53| INFO atc_ne finished [took 14.8359s]
|
||||
07/11/23 03:32:11| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
07/11/23 03:32:56| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
07/11/23 03:36:32| INFO mul_sld_gsq finished [took 294.6812s]
|
||||
07/11/23 03:38:05| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 387.7698s]
|
||||
07/11/23 03:38:18| INFO mul_sld_gs finished [took 400.7660s]
|
||||
07/11/23 03:38:18| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 401.3208s]
|
||||
07/11/23 03:38:18| INFO Dataset sample 0.20 of dataset imdb_9prevs started
|
||||
07/11/23 03:38:30| INFO ref finished [took 11.1665s]
|
||||
07/11/23 03:38:34| INFO atc_mc finished [took 14.4483s]
|
||||
07/11/23 03:38:34| INFO atc_ne finished [took 14.8634s]
|
||||
07/11/23 03:43:16| INFO bin_sld_gsq finished [took 296.8786s]
|
||||
07/11/23 03:43:32| INFO mul_sld_gsq finished [took 312.4588s]
|
||||
07/11/23 03:45:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 445.1331s]
|
||||
07/11/23 03:45:58| INFO mul_sld_gs finished [took 459.5855s]
|
||||
07/11/23 03:51:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 766.1528s]
|
||||
07/11/23 03:53:40| INFO bin_sld_gs finished [took 921.5996s]
|
||||
07/11/23 03:53:40| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 922.0949s]
|
||||
07/11/23 03:53:40| INFO Dataset sample 0.30 of dataset imdb_9prevs started
|
||||
07/11/23 03:53:53| INFO ref finished [took 11.5825s]
|
||||
07/11/23 03:53:57| INFO atc_mc finished [took 14.8590s]
|
||||
07/11/23 03:53:57| INFO atc_ne finished [took 15.3090s]
|
||||
07/11/23 03:58:53| INFO mul_sld_gsq finished [took 311.9891s]
|
||||
07/11/23 03:58:54| INFO bin_sld_gsq finished [took 313.1182s]
|
||||
07/11/23 04:01:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 441.3198s]
|
||||
07/11/23 04:01:18| INFO mul_sld_gs finished [took 456.2347s]
|
||||
07/11/23 04:06:06| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 745.0596s]
|
||||
07/11/23 04:08:40| INFO bin_sld_gs finished [took 898.9046s]
|
||||
07/11/23 04:08:40| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 899.6778s]
|
||||
07/11/23 04:08:40| INFO Dataset sample 0.40 of dataset imdb_9prevs started
|
||||
07/11/23 04:08:52| INFO ref finished [took 11.0605s]
|
||||
07/11/23 04:08:56| INFO atc_mc finished [took 14.9590s]
|
||||
07/11/23 04:08:56| INFO atc_ne finished [took 14.8804s]
|
||||
07/11/23 04:13:54| INFO mul_sld_gsq finished [took 313.3797s]
|
||||
07/11/23 04:13:56| INFO bin_sld_gsq finished [took 315.5862s]
|
||||
07/11/23 04:15:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 432.9025s]
|
||||
07/11/23 04:16:08| INFO mul_sld_gs finished [took 447.1098s]
|
||||
07/11/23 04:21:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 764.2230s]
|
||||
07/11/23 04:23:56| INFO bin_sld_gs finished [took 915.4905s]
|
||||
07/11/23 04:23:56| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 916.1187s]
|
||||
07/11/23 04:23:56| INFO Dataset sample 0.50 of dataset imdb_9prevs started
|
||||
07/11/23 04:24:08| INFO ref finished [took 10.9214s]
|
||||
07/11/23 04:24:12| INFO atc_mc finished [took 14.9236s]
|
||||
07/11/23 04:24:12| INFO atc_ne finished [took 14.9240s]
|
||||
07/11/23 04:29:11| INFO bin_sld_gsq finished [took 314.3071s]
|
||||
07/11/23 04:29:19| INFO mul_sld_gsq finished [took 322.1027s]
|
||||
07/11/23 04:31:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 448.0202s]
|
||||
07/11/23 04:31:40| INFO mul_sld_gs finished [took 463.2243s]
|
||||
07/11/23 04:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 746.2797s]
|
||||
07/11/23 04:38:55| INFO bin_sld_gs finished [took 898.7899s]
|
||||
07/11/23 04:38:55| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 899.2924s]
|
||||
07/11/23 04:38:55| INFO Dataset sample 0.60 of dataset imdb_9prevs started
|
||||
07/11/23 04:39:08| INFO ref finished [took 11.9811s]
|
||||
07/11/23 04:39:12| INFO atc_mc finished [took 15.7159s]
|
||||
07/11/23 04:39:12| INFO atc_ne finished [took 15.9512s]
|
||||
07/11/23 04:44:19| INFO bin_sld_gsq finished [took 323.1420s]
|
||||
07/11/23 04:44:21| INFO mul_sld_gsq finished [took 325.2299s]
|
||||
07/11/23 04:46:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 445.8872s]
|
||||
07/11/23 04:46:37| INFO mul_sld_gs finished [took 460.6339s]
|
||||
07/11/23 04:52:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 786.7500s]
|
||||
07/11/23 04:54:36| INFO bin_sld_gs finished [took 940.1627s]
|
||||
07/11/23 04:54:36| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 940.6023s]
|
||||
07/11/23 04:54:36| INFO Dataset sample 0.70 of dataset imdb_9prevs started
|
||||
07/11/23 04:54:48| INFO ref finished [took 11.1744s]
|
||||
07/11/23 04:54:52| INFO atc_mc finished [took 14.7518s]
|
||||
07/11/23 04:54:52| INFO atc_ne finished [took 14.8147s]
|
||||
07/11/23 04:59:45| INFO bin_sld_gsq finished [took 308.3645s]
|
||||
07/11/23 05:00:07| INFO mul_sld_gsq finished [took 330.3332s]
|
||||
07/11/23 05:02:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 456.8448s]
|
||||
07/11/23 05:02:28| INFO mul_sld_gs finished [took 471.4675s]
|
||||
07/11/23 05:06:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 731.2847s]
|
||||
07/11/23 05:09:19| INFO bin_sld_gs finished [took 882.2200s]
|
||||
07/11/23 05:09:19| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 882.8165s]
|
||||
07/11/23 05:09:19| INFO Dataset sample 0.80 of dataset imdb_9prevs started
|
||||
07/11/23 05:09:31| INFO ref finished [took 11.0645s]
|
||||
07/11/23 05:09:35| INFO atc_mc finished [took 14.7375s]
|
||||
07/11/23 05:09:35| INFO atc_ne finished [took 14.7704s]
|
||||
07/11/23 05:14:22| INFO bin_sld_gsq finished [took 302.1848s]
|
||||
07/11/23 05:14:33| INFO mul_sld_gsq finished [took 313.5459s]
|
||||
07/11/23 05:16:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 438.9863s]
|
||||
07/11/23 05:16:52| INFO mul_sld_gs finished [took 452.7273s]
|
||||
07/11/23 05:21:59| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 759.8355s]
|
||||
07/11/23 05:24:38| INFO bin_sld_gs finished [took 918.7338s]
|
||||
07/11/23 05:24:38| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 919.2981s]
|
||||
07/11/23 05:24:38| INFO Dataset sample 0.90 of dataset imdb_9prevs started
|
||||
07/11/23 05:24:39| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
07/11/23 05:24:39| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
07/11/23 05:24:48| INFO ref finished [took 9.1378s]
|
||||
07/11/23 05:24:51| INFO atc_mc finished [took 12.1603s]
|
||||
07/11/23 05:24:52| INFO atc_ne finished [took 12.3482s]
|
||||
07/11/23 05:25:08| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
07/11/23 05:30:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 353.7904s]
|
||||
07/11/23 05:30:45| INFO mul_sld_gs finished [took 365.9283s]
|
||||
07/11/23 05:30:45| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 366.4930s]
|
||||
06/11/23 05:49:49| INFO dataset imdb_9prevs
|
||||
06/11/23 05:49:57| INFO Dataset sample 0.10 of dataset imdb_9prevs started
|
||||
06/11/23 05:50:12| INFO ref finished [took 13.3064s]
|
||||
06/11/23 05:50:17| INFO atc_mc finished [took 17.3508s]
|
||||
06/11/23 05:50:19| INFO mul_pacc finished [took 20.0802s]
|
||||
06/11/23 05:50:22| INFO mulne_sld finished [took 23.6723s]
|
||||
06/11/23 05:50:24| INFO mulmc_sld finished [took 25.5159s]
|
||||
06/11/23 05:50:39| INFO mul_sld finished [took 40.7099s]
|
||||
06/11/23 05:52:55| INFO bin_pacc finished [took 176.3728s]
|
||||
06/11/23 05:53:05| INFO binmc_sld finished [took 186.8240s]
|
||||
06/11/23 05:53:06| INFO binne_sld finished [took 187.6585s]
|
||||
06/11/23 05:53:07| INFO bin_sld finished [took 189.1728s]
|
||||
06/11/23 05:53:07| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 189.6034s]
|
||||
06/11/23 05:53:07| INFO Dataset sample 0.20 of dataset imdb_9prevs started
|
||||
06/11/23 05:53:22| INFO ref finished [took 13.2778s]
|
||||
06/11/23 05:53:26| INFO atc_mc finished [took 17.4491s]
|
||||
06/11/23 05:53:28| INFO mul_pacc finished [took 19.9359s]
|
||||
06/11/23 05:53:40| INFO mulmc_sld finished [took 31.6686s]
|
||||
06/11/23 05:53:44| INFO mulne_sld finished [took 35.2085s]
|
||||
06/11/23 05:53:44| INFO mul_sld finished [took 36.2502s]
|
||||
06/11/23 05:56:05| INFO bin_pacc finished [took 177.0225s]
|
||||
06/11/23 05:56:13| INFO binmc_sld finished [took 185.4811s]
|
||||
06/11/23 05:56:15| INFO bin_sld finished [took 187.1039s]
|
||||
06/11/23 05:56:16| INFO binne_sld finished [took 187.3163s]
|
||||
06/11/23 05:56:16| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 188.4781s]
|
||||
06/11/23 05:56:16| INFO Dataset sample 0.30 of dataset imdb_9prevs started
|
||||
06/11/23 05:56:31| INFO ref finished [took 13.4513s]
|
||||
06/11/23 05:56:36| INFO atc_mc finished [took 18.1025s]
|
||||
06/11/23 05:56:38| INFO mul_pacc finished [took 20.3997s]
|
||||
06/11/23 05:56:45| INFO mulmc_sld finished [took 28.4298s]
|
||||
06/11/23 05:56:46| INFO mulne_sld finished [took 28.8678s]
|
||||
06/11/23 05:56:46| INFO mul_sld finished [took 29.5573s]
|
||||
06/11/23 05:59:11| INFO bin_pacc finished [took 174.0262s]
|
||||
06/11/23 05:59:17| INFO binmc_sld finished [took 180.1998s]
|
||||
06/11/23 05:59:18| INFO binne_sld finished [took 181.2200s]
|
||||
06/11/23 05:59:19| INFO bin_sld finished [took 182.1672s]
|
||||
06/11/23 05:59:19| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 183.0515s]
|
||||
06/11/23 05:59:19| INFO Dataset sample 0.40 of dataset imdb_9prevs started
|
||||
06/11/23 05:59:34| INFO ref finished [took 13.5163s]
|
||||
06/11/23 05:59:39| INFO atc_mc finished [took 17.9856s]
|
||||
06/11/23 05:59:41| INFO mul_pacc finished [took 20.7441s]
|
||||
06/11/23 05:59:49| INFO mulmc_sld finished [took 29.2747s]
|
||||
06/11/23 05:59:50| INFO mulne_sld finished [took 29.6624s]
|
||||
06/11/23 05:59:50| INFO mul_sld finished [took 30.3432s]
|
||||
06/11/23 06:02:17| INFO bin_pacc finished [took 176.7354s]
|
||||
06/11/23 06:02:19| INFO binmc_sld finished [took 179.9981s]
|
||||
06/11/23 06:02:21| INFO bin_sld finished [took 181.6844s]
|
||||
06/11/23 06:02:22| INFO binne_sld finished [took 182.0846s]
|
||||
06/11/23 06:02:22| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 183.2033s]
|
||||
06/11/23 06:02:22| INFO Dataset sample 0.50 of dataset imdb_9prevs started
|
||||
06/11/23 06:02:37| INFO ref finished [took 13.4688s]
|
||||
06/11/23 06:02:42| INFO atc_mc finished [took 18.0218s]
|
||||
06/11/23 06:02:44| INFO mul_pacc finished [took 20.5800s]
|
||||
06/11/23 06:02:52| INFO mulmc_sld finished [took 29.0192s]
|
||||
06/11/23 06:02:52| INFO mul_sld finished [took 29.4403s]
|
||||
06/11/23 06:02:52| INFO mulne_sld finished [took 29.1611s]
|
||||
06/11/23 06:05:19| INFO bin_pacc finished [took 175.5125s]
|
||||
06/11/23 06:05:23| INFO binmc_sld finished [took 180.0427s]
|
||||
06/11/23 06:05:25| INFO binne_sld finished [took 182.5814s]
|
||||
06/11/23 06:05:26| INFO bin_sld finished [took 183.2892s]
|
||||
06/11/23 06:05:26| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 183.8611s]
|
||||
06/11/23 06:05:26| INFO Dataset sample 0.60 of dataset imdb_9prevs started
|
||||
06/11/23 06:05:41| INFO ref finished [took 13.4643s]
|
||||
06/11/23 06:05:45| INFO atc_mc finished [took 17.9768s]
|
||||
06/11/23 06:05:48| INFO mul_pacc finished [took 20.7525s]
|
||||
06/11/23 06:05:55| INFO mulmc_sld finished [took 28.8234s]
|
||||
06/11/23 06:05:55| INFO mulne_sld finished [took 28.6537s]
|
||||
06/11/23 06:05:56| INFO mul_sld finished [took 29.6167s]
|
||||
06/11/23 06:08:24| INFO bin_pacc finished [took 176.5335s]
|
||||
06/11/23 06:08:27| INFO binmc_sld finished [took 180.4803s]
|
||||
06/11/23 06:08:28| INFO bin_sld finished [took 181.6676s]
|
||||
06/11/23 06:08:29| INFO binne_sld finished [took 182.0534s]
|
||||
06/11/23 06:08:29| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 183.0240s]
|
||||
06/11/23 06:08:29| INFO Dataset sample 0.70 of dataset imdb_9prevs started
|
||||
06/11/23 06:08:44| INFO ref finished [took 13.7566s]
|
||||
06/11/23 06:08:49| INFO atc_mc finished [took 17.9495s]
|
||||
06/11/23 06:08:51| INFO mul_pacc finished [took 20.5859s]
|
||||
06/11/23 06:08:57| INFO mulmc_sld finished [took 27.4370s]
|
||||
06/11/23 06:08:58| INFO mul_sld finished [took 28.3224s]
|
||||
06/11/23 06:08:58| INFO mulne_sld finished [took 28.1390s]
|
||||
06/11/23 06:11:26| INFO bin_pacc finished [took 175.7412s]
|
||||
06/11/23 06:11:31| INFO binmc_sld finished [took 181.4310s]
|
||||
06/11/23 06:11:32| INFO binne_sld finished [took 182.0095s]
|
||||
06/11/23 06:11:33| INFO bin_sld finished [took 183.6520s]
|
||||
06/11/23 06:11:33| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 184.2005s]
|
||||
06/11/23 06:11:33| INFO Dataset sample 0.80 of dataset imdb_9prevs started
|
||||
06/11/23 06:11:48| INFO ref finished [took 13.5418s]
|
||||
06/11/23 06:11:53| INFO atc_mc finished [took 17.8150s]
|
||||
06/11/23 06:11:55| INFO mul_pacc finished [took 20.4761s]
|
||||
06/11/23 06:12:01| INFO mulmc_sld finished [took 27.2741s]
|
||||
06/11/23 06:12:02| INFO mulne_sld finished [took 27.2693s]
|
||||
06/11/23 06:12:02| INFO mul_sld finished [took 28.3364s]
|
||||
06/11/23 06:14:30| INFO bin_pacc finished [took 175.7637s]
|
||||
06/11/23 06:14:37| INFO binmc_sld finished [took 183.2422s]
|
||||
06/11/23 06:14:38| INFO bin_sld finished [took 184.1064s]
|
||||
06/11/23 06:14:39| INFO binne_sld finished [took 184.9073s]
|
||||
06/11/23 06:14:39| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 186.2580s]
|
||||
06/11/23 06:14:39| INFO Dataset sample 0.90 of dataset imdb_9prevs started
|
||||
06/11/23 06:14:41| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:14:41| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:14:52| INFO ref finished [took 11.6315s]
|
||||
06/11/23 06:14:56| INFO atc_mc finished [took 15.3068s]
|
||||
06/11/23 06:15:01| INFO mulne_sld finished [took 21.1133s]
|
||||
06/11/23 06:15:02| INFO mulmc_sld finished [took 22.2375s]
|
||||
06/11/23 06:15:08| INFO mul_sld finished [took 27.8149s]
|
||||
06/11/23 06:17:32| INFO binne_sld finished [took 171.8722s]
|
||||
06/11/23 06:17:32| INFO bin_sld finished [took 172.4710s]
|
||||
06/11/23 06:17:33| INFO binmc_sld finished [took 172.8193s]
|
||||
06/11/23 06:17:33| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 173.4411s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 14:48:04| INFO dataset imdb_9prevs
|
||||
06/11/23 14:48:14| INFO Dataset sample 0.10 of dataset imdb_9prevs started
|
||||
06/11/23 14:48:17| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 14:48:18| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 14:48:31| INFO doc_feat finished [took 11.5257s]
|
||||
06/11/23 14:48:36| INFO ref finished [took 18.5620s]
|
||||
06/11/23 14:48:42| INFO kfcv finished [took 24.7227s]
|
||||
06/11/23 14:48:44| INFO atc_ne finished [took 25.5676s]
|
||||
06/11/23 14:48:46| INFO atc_mc finished [took 27.4910s]
|
||||
06/11/23 14:48:50| INFO mulne_pacc finished [took 34.0415s]
|
||||
06/11/23 14:48:57| INFO mulmc_pacc finished [took 41.7500s]
|
||||
06/11/23 14:48:58| INFO mul_pacc finished [took 43.0162s]
|
||||
06/11/23 14:48:58| INFO mul_cc finished [took 40.3279s]
|
||||
06/11/23 14:49:16| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 14:49:26| INFO mul_sld finished [took 71.4588s]
|
||||
06/11/23 14:50:10| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 14:52:12| INFO binne_pacc finished [took 236.2174s]
|
||||
06/11/23 14:52:16| INFO binmc_pacc finished [took 240.4686s]
|
||||
06/11/23 14:52:19| INFO bin_cc finished [took 241.9141s]
|
||||
06/11/23 14:52:20| INFO bin_pacc finished [took 244.5632s]
|
||||
06/11/23 14:52:23| INFO bin_sld finished [took 249.0477s]
|
||||
06/11/23 14:53:48| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 14:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 443.6010s]
|
||||
06/11/23 14:55:51| INFO mul_sld_gs finished [took 455.9932s]
|
||||
06/11/23 14:55:51| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 456.7746s]
|
||||
06/11/23 14:55:51| INFO Dataset sample 0.20 of dataset imdb_9prevs started
|
||||
06/11/23 14:56:07| INFO doc_feat finished [took 11.2758s]
|
||||
06/11/23 14:56:18| INFO atc_mc finished [took 22.2986s]
|
||||
06/11/23 14:56:22| INFO ref finished [took 26.3482s]
|
||||
06/11/23 14:56:25| INFO kfcv finished [took 30.4761s]
|
||||
06/11/23 14:56:29| INFO mul_pacc finished [took 36.5892s]
|
||||
06/11/23 14:56:29| INFO mulmc_pacc finished [took 36.7773s]
|
||||
06/11/23 14:56:38| INFO atc_ne finished [took 41.7824s]
|
||||
06/11/23 14:56:41| INFO mulne_pacc finished [took 47.8318s]
|
||||
06/11/23 14:56:41| INFO mul_cc finished [took 46.7221s]
|
||||
06/11/23 14:56:55| INFO mul_sld finished [took 63.3547s]
|
||||
06/11/23 14:57:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.01017) [took 119.9166s]
|
||||
06/11/23 14:58:15| INFO mul_pacc_gs finished [took 141.4446s]
|
||||
06/11/23 15:00:38| INFO binne_pacc finished [took 285.5562s]
|
||||
06/11/23 15:00:48| INFO bin_cc finished [took 293.8727s]
|
||||
06/11/23 15:00:49| INFO binmc_pacc finished [took 296.7176s]
|
||||
06/11/23 15:00:49| INFO bin_pacc finished [took 297.1868s]
|
||||
06/11/23 15:01:03| INFO bin_sld finished [took 312.0358s]
|
||||
06/11/23 15:02:29| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:02:34| INFO bin_sld_gsq finished [took 402.0748s]
|
||||
06/11/23 15:03:56| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00980) [took 482.9237s]
|
||||
06/11/23 15:05:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 548.0443s]
|
||||
06/11/23 15:05:14| INFO mul_sld_gs finished [took 562.2966s]
|
||||
06/11/23 15:06:30| INFO bin_pacc_gs finished [took 636.7956s]
|
||||
06/11/23 15:10:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 884.9748s]
|
||||
06/11/23 15:13:11| INFO bin_sld_gs finished [took 1039.3282s]
|
||||
06/11/23 15:13:11| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 1040.0772s]
|
||||
06/11/23 15:13:11| INFO Dataset sample 0.30 of dataset imdb_9prevs started
|
||||
06/11/23 15:13:39| INFO doc_feat finished [took 22.8145s]
|
||||
06/11/23 15:13:41| INFO atc_ne finished [took 24.3471s]
|
||||
06/11/23 15:13:45| INFO ref finished [took 28.7559s]
|
||||
06/11/23 15:13:52| INFO mulne_pacc finished [took 38.1365s]
|
||||
06/11/23 15:13:53| INFO kfcv finished [took 37.4026s]
|
||||
06/11/23 15:13:56| INFO atc_mc finished [took 39.4198s]
|
||||
06/11/23 15:13:59| INFO mul_pacc finished [took 45.9542s]
|
||||
06/11/23 15:13:59| INFO mul_cc finished [took 43.9076s]
|
||||
06/11/23 15:13:59| INFO mulmc_pacc finished [took 45.9395s]
|
||||
06/11/23 15:14:11| INFO mul_sld finished [took 59.8835s]
|
||||
06/11/23 15:15:23| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01028) [took 128.2866s]
|
||||
06/11/23 15:15:44| INFO mul_pacc_gs finished [took 149.5820s]
|
||||
06/11/23 15:18:03| INFO binne_pacc finished [took 289.3504s]
|
||||
06/11/23 15:18:07| INFO bin_pacc finished [took 294.7115s]
|
||||
06/11/23 15:18:14| INFO bin_cc finished [took 298.6839s]
|
||||
06/11/23 15:18:14| INFO binmc_pacc finished [took 300.9499s]
|
||||
06/11/23 15:18:14| INFO bin_sld finished [took 302.9035s]
|
||||
06/11/23 15:19:46| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:20:05| INFO bin_sld_gsq finished [took 413.1151s]
|
||||
06/11/23 15:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00916) [took 488.7327s]
|
||||
06/11/23 15:22:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 541.2865s]
|
||||
06/11/23 15:22:28| INFO mul_sld_gs finished [took 556.0867s]
|
||||
06/11/23 15:23:57| INFO bin_pacc_gs finished [took 643.0717s]
|
||||
06/11/23 15:27:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 860.3135s]
|
||||
06/11/23 15:30:05| INFO bin_sld_gs finished [took 1013.1878s]
|
||||
06/11/23 15:30:05| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 1014.3141s]
|
||||
06/11/23 15:30:05| INFO Dataset sample 0.40 of dataset imdb_9prevs started
|
||||
06/11/23 15:30:24| INFO doc_feat finished [took 13.8500s]
|
||||
06/11/23 15:30:32| INFO ref finished [took 22.3531s]
|
||||
06/11/23 15:30:41| INFO mul_pacc finished [took 34.1860s]
|
||||
06/11/23 15:30:45| INFO atc_ne finished [took 34.8111s]
|
||||
06/11/23 15:30:46| INFO kfcv finished [took 36.4055s]
|
||||
06/11/23 15:30:49| INFO atc_mc finished [took 38.7978s]
|
||||
06/11/23 15:30:49| INFO mulmc_pacc finished [took 42.4552s]
|
||||
06/11/23 15:30:51| INFO mul_cc finished [took 42.6899s]
|
||||
06/11/23 15:30:53| INFO mulne_pacc finished [took 45.2694s]
|
||||
06/11/23 15:30:57| INFO mul_sld finished [took 51.2705s]
|
||||
06/11/23 15:32:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01220) [took 124.5801s]
|
||||
06/11/23 15:32:34| INFO mul_pacc_gs finished [took 145.3368s]
|
||||
06/11/23 15:34:56| INFO binmc_pacc finished [took 289.1451s]
|
||||
06/11/23 15:35:04| INFO bin_sld finished [took 298.3514s]
|
||||
06/11/23 15:35:04| INFO binne_pacc finished [took 296.5538s]
|
||||
06/11/23 15:35:05| INFO bin_pacc finished [took 298.5077s]
|
||||
06/11/23 15:35:09| INFO bin_cc finished [took 300.1332s]
|
||||
06/11/23 15:36:41| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:37:08| INFO bin_sld_gsq finished [took 421.3938s]
|
||||
06/11/23 15:38:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01137) [took 490.9644s]
|
||||
06/11/23 15:38:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 531.8225s]
|
||||
06/11/23 15:39:12| INFO mul_sld_gs finished [took 546.4524s]
|
||||
06/11/23 15:40:53| INFO bin_pacc_gs finished [took 645.0957s]
|
||||
06/11/23 15:44:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 882.0550s]
|
||||
06/11/23 15:47:19| INFO bin_sld_gs finished [took 1033.2802s]
|
||||
06/11/23 15:47:19| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 1034.1241s]
|
||||
06/11/23 15:47:19| INFO Dataset sample 0.50 of dataset imdb_9prevs started
|
||||
06/11/23 15:47:36| INFO doc_feat finished [took 11.6005s]
|
||||
06/11/23 15:47:40| INFO ref finished [took 16.3058s]
|
||||
06/11/23 15:47:50| INFO atc_mc finished [took 25.8745s]
|
||||
06/11/23 15:47:52| INFO kfcv finished [took 29.0931s]
|
||||
06/11/23 15:47:53| INFO atc_ne finished [took 28.8903s]
|
||||
06/11/23 15:47:53| INFO mul_pacc finished [took 32.5473s]
|
||||
06/11/23 15:48:00| INFO mul_cc finished [took 37.3478s]
|
||||
06/11/23 15:48:01| INFO mulne_pacc finished [took 39.9745s]
|
||||
06/11/23 15:48:02| INFO mulmc_pacc finished [took 40.5057s]
|
||||
06/11/23 15:48:10| INFO mul_sld finished [took 50.1825s]
|
||||
06/11/23 15:49:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01107) [took 125.0329s]
|
||||
06/11/23 15:49:49| INFO mul_pacc_gs finished [took 146.7316s]
|
||||
06/11/23 15:52:15| INFO bin_cc finished [took 292.6719s]
|
||||
06/11/23 15:52:15| INFO binne_pacc finished [took 293.9844s]
|
||||
06/11/23 15:52:17| INFO bin_pacc finished [took 296.2830s]
|
||||
06/11/23 15:52:21| INFO binmc_pacc finished [took 299.4873s]
|
||||
06/11/23 15:52:23| INFO bin_sld finished [took 303.4889s]
|
||||
06/11/23 15:53:57| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 15:54:18| INFO bin_sld_gsq finished [took 418.0959s]
|
||||
06/11/23 15:55:32| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 489.7797s]
|
||||
06/11/23 15:56:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 536.7408s]
|
||||
06/11/23 15:56:33| INFO mul_sld_gs finished [took 552.5393s]
|
||||
06/11/23 15:58:05| INFO bin_pacc_gs finished [took 643.1581s]
|
||||
06/11/23 16:01:42| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 862.6012s]
|
||||
06/11/23 16:04:15| INFO bin_sld_gs finished [took 1015.3606s]
|
||||
06/11/23 16:04:15| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 1016.0642s]
|
||||
06/11/23 16:04:15| INFO Dataset sample 0.60 of dataset imdb_9prevs started
|
||||
06/11/23 16:04:40| INFO doc_feat finished [took 19.9628s]
|
||||
06/11/23 16:04:41| INFO kfcv finished [took 21.8848s]
|
||||
06/11/23 16:04:46| INFO ref finished [took 26.2613s]
|
||||
06/11/23 16:04:56| INFO mulmc_pacc finished [took 38.6399s]
|
||||
06/11/23 16:04:56| INFO atc_ne finished [took 35.7501s]
|
||||
06/11/23 16:04:57| INFO atc_mc finished [took 37.3907s]
|
||||
06/11/23 16:05:01| INFO mul_cc finished [took 41.6420s]
|
||||
06/11/23 16:05:01| INFO mul_pacc finished [took 44.6898s]
|
||||
06/11/23 16:05:02| INFO mulne_pacc finished [took 44.7679s]
|
||||
06/11/23 16:05:12| INFO mul_sld finished [took 56.0834s]
|
||||
06/11/23 16:06:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01082) [took 125.2569s]
|
||||
06/11/23 16:06:44| INFO mul_pacc_gs finished [took 146.2318s]
|
||||
06/11/23 16:09:05| INFO binne_pacc finished [took 288.1949s]
|
||||
06/11/23 16:09:10| INFO bin_pacc finished [took 293.3207s]
|
||||
06/11/23 16:09:12| INFO bin_sld finished [took 296.1022s]
|
||||
06/11/23 16:09:13| INFO binmc_pacc finished [took 296.4000s]
|
||||
06/11/23 16:09:18| INFO bin_cc finished [took 299.1982s]
|
||||
06/11/23 16:10:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 16:11:22| INFO bin_sld_gsq finished [took 425.6641s]
|
||||
06/11/23 16:12:31| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00976) [took 492.8847s]
|
||||
06/11/23 16:13:13| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 536.8669s]
|
||||
06/11/23 16:13:28| INFO mul_sld_gs finished [took 551.6187s]
|
||||
06/11/23 16:15:03| INFO bin_pacc_gs finished [took 645.6602s]
|
||||
06/11/23 16:19:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 907.7074s]
|
||||
06/11/23 16:21:57| INFO bin_sld_gs finished [took 1060.9759s]
|
||||
06/11/23 16:21:57| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 1061.7730s]
|
||||
06/11/23 16:21:57| INFO Dataset sample 0.70 of dataset imdb_9prevs started
|
||||
06/11/23 16:22:23| INFO doc_feat finished [took 20.2428s]
|
||||
06/11/23 16:22:34| INFO kfcv finished [took 32.1532s]
|
||||
06/11/23 16:22:36| INFO ref finished [took 34.3738s]
|
||||
06/11/23 16:22:38| INFO mul_sld finished [took 40.1101s]
|
||||
06/11/23 16:22:40| INFO mul_cc finished [took 38.6722s]
|
||||
06/11/23 16:22:41| INFO atc_mc finished [took 38.9379s]
|
||||
06/11/23 16:22:43| INFO atc_ne finished [took 40.3132s]
|
||||
06/11/23 16:22:43| INFO mulne_pacc finished [took 43.7833s]
|
||||
06/11/23 16:22:44| INFO mulmc_pacc finished [took 44.4084s]
|
||||
06/11/23 16:22:46| INFO mul_pacc finished [took 47.7998s]
|
||||
06/11/23 16:24:08| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01575) [took 127.2393s]
|
||||
06/11/23 16:24:31| INFO mul_pacc_gs finished [took 150.2100s]
|
||||
06/11/23 16:26:49| INFO bin_cc finished [took 288.6128s]
|
||||
06/11/23 16:26:51| INFO bin_pacc finished [took 292.1757s]
|
||||
06/11/23 16:26:52| INFO binne_pacc finished [took 293.0194s]
|
||||
06/11/23 16:27:01| INFO binmc_pacc finished [took 302.5703s]
|
||||
06/11/23 16:27:01| INFO bin_sld finished [took 303.9303s]
|
||||
06/11/23 16:28:32| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 16:28:53| INFO bin_sld_gsq finished [took 414.4520s]
|
||||
06/11/23 16:30:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01641) [took 494.7681s]
|
||||
06/11/23 16:31:00| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 542.3282s]
|
||||
06/11/23 16:31:15| INFO mul_sld_gs finished [took 557.2859s]
|
||||
06/11/23 16:32:49| INFO bin_pacc_gs finished [took 648.9428s]
|
||||
06/11/23 16:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 864.7237s]
|
||||
06/11/23 16:38:54| INFO bin_sld_gs finished [took 1015.9618s]
|
||||
06/11/23 16:38:54| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 1016.7743s]
|
||||
06/11/23 16:38:54| INFO Dataset sample 0.80 of dataset imdb_9prevs started
|
||||
06/11/23 16:39:19| INFO doc_feat finished [took 19.9639s]
|
||||
06/11/23 16:39:22| INFO atc_mc finished [took 22.9650s]
|
||||
06/11/23 16:39:26| INFO kfcv finished [took 27.9671s]
|
||||
06/11/23 16:39:30| INFO mul_pacc finished [took 34.3899s]
|
||||
06/11/23 16:39:31| INFO ref finished [took 32.4692s]
|
||||
06/11/23 16:39:33| INFO mulne_pacc finished [took 37.2045s]
|
||||
06/11/23 16:39:39| INFO atc_ne finished [took 39.7686s]
|
||||
06/11/23 16:39:41| INFO mul_cc finished [took 42.9411s]
|
||||
06/11/23 16:39:41| INFO mulmc_pacc finished [took 44.9724s]
|
||||
06/11/23 16:39:46| INFO mul_sld finished [took 51.4269s]
|
||||
06/11/23 16:40:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01013) [took 122.2196s]
|
||||
06/11/23 16:41:24| INFO mul_pacc_gs finished [took 146.7076s]
|
||||
06/11/23 16:43:40| INFO binne_pacc finished [took 284.1154s]
|
||||
06/11/23 16:43:52| INFO bin_pacc finished [took 296.8885s]
|
||||
06/11/23 16:43:54| INFO bin_cc finished [took 297.1714s]
|
||||
06/11/23 16:43:56| INFO binmc_pacc finished [took 300.6806s]
|
||||
06/11/23 16:43:57| INFO bin_sld finished [took 302.6966s]
|
||||
06/11/23 16:45:26| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 16:45:41| INFO bin_sld_gsq finished [took 405.8247s]
|
||||
06/11/23 16:47:00| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00949) [took 483.3129s]
|
||||
06/11/23 16:47:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 539.6504s]
|
||||
06/11/23 16:48:09| INFO mul_sld_gs finished [took 553.8401s]
|
||||
06/11/23 16:49:34| INFO bin_pacc_gs finished [took 637.2772s]
|
||||
06/11/23 16:53:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 875.8870s]
|
||||
06/11/23 16:56:08| INFO bin_sld_gs finished [took 1033.4325s]
|
||||
06/11/23 16:56:08| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 1034.1983s]
|
||||
06/11/23 16:56:08| INFO Dataset sample 0.90 of dataset imdb_9prevs started
|
||||
06/11/23 16:56:09| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:09| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:10| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:11| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:11| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 16:56:22| INFO doc_feat finished [took 10.1613s]
|
||||
06/11/23 16:56:25| INFO ref finished [took 13.7569s]
|
||||
06/11/23 16:56:27| INFO kfcv finished [took 15.6337s]
|
||||
06/11/23 16:56:29| INFO atc_mc finished [took 18.0104s]
|
||||
06/11/23 16:56:30| INFO atc_ne finished [took 18.0260s]
|
||||
06/11/23 16:56:31| INFO mul_cc finished [took 20.6201s]
|
||||
06/11/23 16:56:40| INFO mul_sld finished [took 31.2942s]
|
||||
06/11/23 16:56:47| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 16:58:55| INFO bin_cc finished [took 164.5182s]
|
||||
06/11/23 16:58:59| INFO bin_sld finished [took 170.5046s]
|
||||
06/11/23 17:02:17| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 368.6067s]
|
||||
06/11/23 17:02:29| INFO mul_sld_gs finished [took 380.7801s]
|
||||
06/11/23 17:02:29| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 381.5305s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
07/11/23 03:31:29| INFO dataset imdb_9prevs
|
||||
07/11/23 03:31:37| INFO Dataset sample 0.10 of dataset imdb_9prevs started
|
||||
07/11/23 03:31:49| INFO ref finished [took 11.4117s]
|
||||
07/11/23 03:31:53| INFO atc_mc finished [took 14.8218s]
|
||||
07/11/23 03:31:53| INFO atc_ne finished [took 14.8359s]
|
||||
07/11/23 03:32:11| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
07/11/23 03:32:56| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
07/11/23 03:36:32| INFO mul_sld_gsq finished [took 294.6812s]
|
||||
07/11/23 03:38:05| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.03127) [took 387.7698s]
|
||||
07/11/23 03:38:18| INFO mul_sld_gs finished [took 400.7660s]
|
||||
07/11/23 03:38:18| INFO Dataset sample 0.10 of dataset imdb_9prevs finished [took 401.3208s]
|
||||
07/11/23 03:38:18| INFO Dataset sample 0.20 of dataset imdb_9prevs started
|
||||
07/11/23 03:38:30| INFO ref finished [took 11.1665s]
|
||||
07/11/23 03:38:34| INFO atc_mc finished [took 14.4483s]
|
||||
07/11/23 03:38:34| INFO atc_ne finished [took 14.8634s]
|
||||
07/11/23 03:43:16| INFO bin_sld_gsq finished [took 296.8786s]
|
||||
07/11/23 03:43:32| INFO mul_sld_gsq finished [took 312.4588s]
|
||||
07/11/23 03:45:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01194) [took 445.1331s]
|
||||
07/11/23 03:45:58| INFO mul_sld_gs finished [took 459.5855s]
|
||||
07/11/23 03:51:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00924) [took 766.1528s]
|
||||
07/11/23 03:53:40| INFO bin_sld_gs finished [took 921.5996s]
|
||||
07/11/23 03:53:40| INFO Dataset sample 0.20 of dataset imdb_9prevs finished [took 922.0949s]
|
||||
07/11/23 03:53:40| INFO Dataset sample 0.30 of dataset imdb_9prevs started
|
||||
07/11/23 03:53:53| INFO ref finished [took 11.5825s]
|
||||
07/11/23 03:53:57| INFO atc_mc finished [took 14.8590s]
|
||||
07/11/23 03:53:57| INFO atc_ne finished [took 15.3090s]
|
||||
07/11/23 03:58:53| INFO mul_sld_gsq finished [took 311.9891s]
|
||||
07/11/23 03:58:54| INFO bin_sld_gsq finished [took 313.1182s]
|
||||
07/11/23 04:01:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00953) [took 441.3198s]
|
||||
07/11/23 04:01:18| INFO mul_sld_gs finished [took 456.2347s]
|
||||
07/11/23 04:06:06| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01064) [took 745.0596s]
|
||||
07/11/23 04:08:40| INFO bin_sld_gs finished [took 898.9046s]
|
||||
07/11/23 04:08:40| INFO Dataset sample 0.30 of dataset imdb_9prevs finished [took 899.6778s]
|
||||
07/11/23 04:08:40| INFO Dataset sample 0.40 of dataset imdb_9prevs started
|
||||
07/11/23 04:08:52| INFO ref finished [took 11.0605s]
|
||||
07/11/23 04:08:56| INFO atc_mc finished [took 14.9590s]
|
||||
07/11/23 04:08:56| INFO atc_ne finished [took 14.8804s]
|
||||
07/11/23 04:13:54| INFO mul_sld_gsq finished [took 313.3797s]
|
||||
07/11/23 04:13:56| INFO bin_sld_gsq finished [took 315.5862s]
|
||||
07/11/23 04:15:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01029) [took 432.9025s]
|
||||
07/11/23 04:16:08| INFO mul_sld_gs finished [took 447.1098s]
|
||||
07/11/23 04:21:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01176) [took 764.2230s]
|
||||
07/11/23 04:23:56| INFO bin_sld_gs finished [took 915.4905s]
|
||||
07/11/23 04:23:56| INFO Dataset sample 0.40 of dataset imdb_9prevs finished [took 916.1187s]
|
||||
07/11/23 04:23:56| INFO Dataset sample 0.50 of dataset imdb_9prevs started
|
||||
07/11/23 04:24:08| INFO ref finished [took 10.9214s]
|
||||
07/11/23 04:24:12| INFO atc_mc finished [took 14.9236s]
|
||||
07/11/23 04:24:12| INFO atc_ne finished [took 14.9240s]
|
||||
07/11/23 04:29:11| INFO bin_sld_gsq finished [took 314.3071s]
|
||||
07/11/23 04:29:19| INFO mul_sld_gsq finished [took 322.1027s]
|
||||
07/11/23 04:31:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00885) [took 448.0202s]
|
||||
07/11/23 04:31:40| INFO mul_sld_gs finished [took 463.2243s]
|
||||
07/11/23 04:36:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00940) [took 746.2797s]
|
||||
07/11/23 04:38:55| INFO bin_sld_gs finished [took 898.7899s]
|
||||
07/11/23 04:38:55| INFO Dataset sample 0.50 of dataset imdb_9prevs finished [took 899.2924s]
|
||||
07/11/23 04:38:55| INFO Dataset sample 0.60 of dataset imdb_9prevs started
|
||||
07/11/23 04:39:08| INFO ref finished [took 11.9811s]
|
||||
07/11/23 04:39:12| INFO atc_mc finished [took 15.7159s]
|
||||
07/11/23 04:39:12| INFO atc_ne finished [took 15.9512s]
|
||||
07/11/23 04:44:19| INFO bin_sld_gsq finished [took 323.1420s]
|
||||
07/11/23 04:44:21| INFO mul_sld_gsq finished [took 325.2299s]
|
||||
07/11/23 04:46:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00984) [took 445.8872s]
|
||||
07/11/23 04:46:37| INFO mul_sld_gs finished [took 460.6339s]
|
||||
07/11/23 04:52:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.01142) [took 786.7500s]
|
||||
07/11/23 04:54:36| INFO bin_sld_gs finished [took 940.1627s]
|
||||
07/11/23 04:54:36| INFO Dataset sample 0.60 of dataset imdb_9prevs finished [took 940.6023s]
|
||||
07/11/23 04:54:36| INFO Dataset sample 0.70 of dataset imdb_9prevs started
|
||||
07/11/23 04:54:48| INFO ref finished [took 11.1744s]
|
||||
07/11/23 04:54:52| INFO atc_mc finished [took 14.7518s]
|
||||
07/11/23 04:54:52| INFO atc_ne finished [took 14.8147s]
|
||||
07/11/23 04:59:45| INFO bin_sld_gsq finished [took 308.3645s]
|
||||
07/11/23 05:00:07| INFO mul_sld_gsq finished [took 330.3332s]
|
||||
07/11/23 05:02:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01102) [took 456.8448s]
|
||||
07/11/23 05:02:28| INFO mul_sld_gs finished [took 471.4675s]
|
||||
07/11/23 05:06:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.02196) [took 731.2847s]
|
||||
07/11/23 05:09:19| INFO bin_sld_gs finished [took 882.2200s]
|
||||
07/11/23 05:09:19| INFO Dataset sample 0.70 of dataset imdb_9prevs finished [took 882.8165s]
|
||||
07/11/23 05:09:19| INFO Dataset sample 0.80 of dataset imdb_9prevs started
|
||||
07/11/23 05:09:31| INFO ref finished [took 11.0645s]
|
||||
07/11/23 05:09:35| INFO atc_mc finished [took 14.7375s]
|
||||
07/11/23 05:09:35| INFO atc_ne finished [took 14.7704s]
|
||||
07/11/23 05:14:22| INFO bin_sld_gsq finished [took 302.1848s]
|
||||
07/11/23 05:14:33| INFO mul_sld_gsq finished [took 313.5459s]
|
||||
07/11/23 05:16:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00785) [took 438.9863s]
|
||||
07/11/23 05:16:52| INFO mul_sld_gs finished [took 452.7273s]
|
||||
07/11/23 05:21:59| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01449) [took 759.8355s]
|
||||
07/11/23 05:24:38| INFO bin_sld_gs finished [took 918.7338s]
|
||||
07/11/23 05:24:38| INFO Dataset sample 0.80 of dataset imdb_9prevs finished [took 919.2981s]
|
||||
07/11/23 05:24:38| INFO Dataset sample 0.90 of dataset imdb_9prevs started
|
||||
07/11/23 05:24:39| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
07/11/23 05:24:39| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
07/11/23 05:24:48| INFO ref finished [took 9.1378s]
|
||||
07/11/23 05:24:51| INFO atc_mc finished [took 12.1603s]
|
||||
07/11/23 05:24:52| INFO atc_ne finished [took 12.3482s]
|
||||
07/11/23 05:25:08| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
07/11/23 05:30:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.04178) [took 353.7904s]
|
||||
07/11/23 05:30:45| INFO mul_sld_gs finished [took 365.9283s]
|
||||
07/11/23 05:30:45| INFO Dataset sample 0.90 of dataset imdb_9prevs finished [took 366.4930s]
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
|
|
@ -1,455 +1,455 @@
|
|||
06/11/23 05:14:48| INFO dataset rcv1_CCAT_9prevs
|
||||
06/11/23 05:14:53| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:15:55| INFO ref finished [took 48.0242s]
|
||||
06/11/23 05:16:01| INFO atc_mc finished [took 51.7851s]
|
||||
06/11/23 05:16:04| INFO mul_pacc finished [took 58.4704s]
|
||||
06/11/23 05:16:04| INFO mulne_sld finished [took 62.7354s]
|
||||
06/11/23 05:16:04| INFO mulmc_sld finished [took 66.2593s]
|
||||
06/11/23 05:16:14| INFO mul_sld finished [took 78.2483s]
|
||||
06/11/23 05:18:40| INFO bin_pacc finished [took 217.0012s]
|
||||
06/11/23 05:18:43| INFO bin_sld finished [took 227.8835s]
|
||||
06/11/23 05:18:43| INFO binne_sld finished [took 223.2764s]
|
||||
06/11/23 05:18:44| INFO binmc_sld finished [took 226.7324s]
|
||||
06/11/23 05:18:44| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 230.5906s]
|
||||
06/11/23 05:18:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:19:44| INFO ref finished [took 49.5147s]
|
||||
06/11/23 05:19:51| INFO atc_mc finished [took 54.8022s]
|
||||
06/11/23 05:19:53| INFO mul_pacc finished [took 60.3260s]
|
||||
06/11/23 05:19:55| INFO mulmc_sld finished [took 67.0280s]
|
||||
06/11/23 05:19:56| INFO mul_sld finished [took 70.4092s]
|
||||
06/11/23 05:19:58| INFO mulne_sld finished [took 67.3468s]
|
||||
06/11/23 05:22:30| INFO bin_sld finished [took 224.7344s]
|
||||
06/11/23 05:22:30| INFO bin_pacc finished [took 218.3044s]
|
||||
06/11/23 05:22:30| INFO binmc_sld finished [took 223.3607s]
|
||||
06/11/23 05:22:33| INFO binne_sld finished [took 223.6042s]
|
||||
06/11/23 05:22:33| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 229.0745s]
|
||||
06/11/23 05:22:33| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:23:32| INFO ref finished [took 48.1565s]
|
||||
06/11/23 05:23:37| INFO atc_mc finished [took 52.1124s]
|
||||
06/11/23 05:23:40| INFO mul_pacc finished [took 58.0112s]
|
||||
06/11/23 05:23:40| INFO mul_sld finished [took 65.2727s]
|
||||
06/11/23 05:23:42| INFO mulmc_sld finished [took 64.5943s]
|
||||
06/11/23 05:23:43| INFO mulne_sld finished [took 63.9053s]
|
||||
06/11/23 05:26:13| INFO bin_sld finished [took 218.6511s]
|
||||
06/11/23 05:26:16| INFO bin_pacc finished [took 215.1485s]
|
||||
06/11/23 05:26:17| INFO binne_sld finished [took 218.6855s]
|
||||
06/11/23 05:26:17| INFO binmc_sld finished [took 221.2605s]
|
||||
06/11/23 05:26:17| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 224.5608s]
|
||||
06/11/23 05:26:17| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:27:15| INFO ref finished [took 48.2181s]
|
||||
06/11/23 05:27:21| INFO atc_mc finished [took 52.3420s]
|
||||
06/11/23 05:27:23| INFO mul_pacc finished [took 57.1950s]
|
||||
06/11/23 05:27:24| INFO mul_sld finished [took 64.4722s]
|
||||
06/11/23 05:27:26| INFO mulmc_sld finished [took 64.1870s]
|
||||
06/11/23 05:27:27| INFO mulne_sld finished [took 63.7407s]
|
||||
06/11/23 05:29:52| INFO bin_sld finished [took 213.1913s]
|
||||
06/11/23 05:29:53| INFO bin_pacc finished [took 208.1322s]
|
||||
06/11/23 05:29:53| INFO binmc_sld finished [took 212.6473s]
|
||||
06/11/23 05:29:57| INFO binne_sld finished [took 214.5243s]
|
||||
06/11/23 05:29:57| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 219.5765s]
|
||||
06/11/23 05:29:57| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:30:55| INFO ref finished [took 47.7289s]
|
||||
06/11/23 05:31:01| INFO atc_mc finished [took 52.1531s]
|
||||
06/11/23 05:31:03| INFO mul_pacc finished [took 57.3804s]
|
||||
06/11/23 05:31:06| INFO mul_sld finished [took 66.9237s]
|
||||
06/11/23 05:31:06| INFO mulmc_sld finished [took 65.3230s]
|
||||
06/11/23 05:31:09| INFO mulne_sld finished [took 65.6645s]
|
||||
06/11/23 05:33:33| INFO bin_sld finished [took 214.3242s]
|
||||
06/11/23 05:33:34| INFO bin_pacc finished [took 209.3862s]
|
||||
06/11/23 05:33:35| INFO binmc_sld finished [took 214.4687s]
|
||||
06/11/23 05:33:37| INFO binne_sld finished [took 214.7267s]
|
||||
06/11/23 05:33:37| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 220.0212s]
|
||||
06/11/23 05:33:37| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:34:35| INFO ref finished [took 48.0021s]
|
||||
06/11/23 05:34:41| INFO atc_mc finished [took 52.2171s]
|
||||
06/11/23 05:34:43| INFO mul_pacc finished [took 57.2348s]
|
||||
06/11/23 05:34:46| INFO mul_sld finished [took 67.0899s]
|
||||
06/11/23 05:34:47| INFO mulmc_sld finished [took 66.1078s]
|
||||
06/11/23 05:34:49| INFO mulne_sld finished [took 66.0237s]
|
||||
06/11/23 05:37:13| INFO bin_sld finished [took 214.9942s]
|
||||
06/11/23 05:37:13| INFO binmc_sld finished [took 213.1574s]
|
||||
06/11/23 05:37:14| INFO bin_pacc finished [took 209.1347s]
|
||||
06/11/23 05:37:17| INFO binne_sld finished [took 214.9703s]
|
||||
06/11/23 05:37:17| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 220.1235s]
|
||||
06/11/23 05:37:17| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:38:15| INFO ref finished [took 47.8227s]
|
||||
06/11/23 05:38:20| INFO atc_mc finished [took 51.9364s]
|
||||
06/11/23 05:38:23| INFO mul_pacc finished [took 56.9053s]
|
||||
06/11/23 05:38:27| INFO mul_sld finished [took 67.4535s]
|
||||
06/11/23 05:38:27| INFO mulmc_sld finished [took 65.5956s]
|
||||
06/11/23 05:38:30| INFO mulne_sld finished [took 66.0476s]
|
||||
06/11/23 05:40:55| INFO bin_pacc finished [took 210.0633s]
|
||||
06/11/23 05:40:56| INFO binmc_sld finished [took 215.3452s]
|
||||
06/11/23 05:40:56| INFO bin_sld finished [took 217.8091s]
|
||||
06/11/23 05:40:59| INFO binne_sld finished [took 216.8970s]
|
||||
06/11/23 05:40:59| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 222.2971s]
|
||||
06/11/23 05:40:59| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:41:57| INFO ref finished [took 47.6970s]
|
||||
06/11/23 05:42:03| INFO atc_mc finished [took 52.0893s]
|
||||
06/11/23 05:42:05| INFO mul_pacc finished [took 56.6428s]
|
||||
06/11/23 05:42:09| INFO mul_sld finished [took 66.8810s]
|
||||
06/11/23 05:42:09| INFO mulmc_sld finished [took 65.8427s]
|
||||
06/11/23 05:42:11| INFO mulne_sld finished [took 64.8594s]
|
||||
06/11/23 05:44:36| INFO bin_pacc finished [took 208.7884s]
|
||||
06/11/23 05:44:38| INFO bin_sld finished [took 216.6052s]
|
||||
06/11/23 05:44:38| INFO binmc_sld finished [took 215.5486s]
|
||||
06/11/23 05:44:43| INFO binne_sld finished [took 217.9926s]
|
||||
06/11/23 05:44:43| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 223.2270s]
|
||||
06/11/23 05:44:43| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:45:40| INFO ref finished [took 48.0710s]
|
||||
06/11/23 05:45:46| INFO atc_mc finished [took 52.0992s]
|
||||
06/11/23 05:45:48| INFO mul_pacc finished [took 56.6568s]
|
||||
06/11/23 05:45:49| INFO mulmc_sld finished [took 61.7314s]
|
||||
06/11/23 05:45:52| INFO mulne_sld finished [took 62.7505s]
|
||||
06/11/23 05:45:59| INFO mul_sld finished [took 73.7681s]
|
||||
06/11/23 05:48:18| INFO bin_pacc finished [took 208.2267s]
|
||||
06/11/23 05:48:23| INFO bin_sld finished [took 218.9333s]
|
||||
06/11/23 05:48:24| INFO binmc_sld finished [took 218.0032s]
|
||||
06/11/23 05:48:27| INFO binne_sld finished [took 219.2450s]
|
||||
06/11/23 05:48:27| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 224.3446s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 11:53:50| INFO dataset rcv1_CCAT_9prevs
|
||||
06/11/23 11:53:56| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 11:56:45| INFO doc_feat finished [took 83.7957s]
|
||||
06/11/23 11:56:58| INFO mulne_pacc finished [took 146.6577s]
|
||||
06/11/23 11:57:03| INFO ref finished [took 120.2665s]
|
||||
06/11/23 11:57:05| INFO mul_pacc finished [took 169.5909s]
|
||||
06/11/23 11:57:07| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 11:57:08| INFO kfcv finished [took 130.0948s]
|
||||
06/11/23 11:57:13| INFO mulmc_pacc finished [took 173.0431s]
|
||||
06/11/23 11:57:16| INFO atc_mc finished [took 125.2363s]
|
||||
06/11/23 11:57:17| INFO mul_sld finished [took 199.1179s]
|
||||
06/11/23 11:57:18| INFO mul_cc finished [took 148.2203s]
|
||||
06/11/23 11:57:20| INFO atc_ne finished [took 121.9570s]
|
||||
06/11/23 11:57:39| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00899) [took 176.8809s]
|
||||
06/11/23 11:58:48| INFO mul_pacc_gs finished [took 245.7641s]
|
||||
06/11/23 12:00:56| INFO bin_pacc finished [took 409.8967s]
|
||||
06/11/23 12:01:03| INFO bin_sld finished [took 426.0031s]
|
||||
06/11/23 12:01:09| INFO binmc_pacc finished [took 412.9057s]
|
||||
06/11/23 12:01:13| INFO bin_cc finished [took 389.4719s]
|
||||
06/11/23 12:01:14| INFO binne_pacc finished [took 411.1276s]
|
||||
06/11/23 12:02:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:03:18| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00719) [took 523.4665s]
|
||||
06/11/23 12:04:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 643.3372s]
|
||||
06/11/23 12:05:27| INFO mul_sld_gs finished [took 686.5912s]
|
||||
06/11/23 12:06:25| INFO bin_pacc_gs finished [took 710.5248s]
|
||||
06/11/23 12:08:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 892.3454s]
|
||||
06/11/23 12:11:50| INFO bin_sld_gs finished [took 1070.2847s]
|
||||
06/11/23 12:11:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 1073.7689s]
|
||||
06/11/23 12:11:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 12:14:15| INFO doc_feat finished [took 80.2198s]
|
||||
06/11/23 12:14:27| INFO ref finished [took 106.1446s]
|
||||
06/11/23 12:14:36| INFO mul_pacc finished [took 155.8715s]
|
||||
06/11/23 12:14:37| INFO mul_sld finished [took 162.7857s]
|
||||
06/11/23 12:14:47| INFO kfcv finished [took 132.1178s]
|
||||
06/11/23 12:14:55| INFO atc_mc finished [took 127.9109s]
|
||||
06/11/23 12:14:57| INFO atc_ne finished [took 121.6128s]
|
||||
06/11/23 12:14:58| INFO mulmc_pacc finished [took 173.9023s]
|
||||
06/11/23 12:14:58| INFO mulne_pacc finished [took 167.2920s]
|
||||
06/11/23 12:14:59| INFO mul_cc finished [took 147.7428s]
|
||||
06/11/23 12:15:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00931) [took 186.6087s]
|
||||
06/11/23 12:16:44| INFO mul_pacc_gs finished [took 261.9352s]
|
||||
06/11/23 12:18:49| INFO binmc_pacc finished [took 407.0394s]
|
||||
06/11/23 12:18:50| INFO bin_pacc finished [took 410.4620s]
|
||||
06/11/23 12:18:55| INFO bin_sld finished [took 422.8949s]
|
||||
06/11/23 12:19:01| INFO binne_pacc finished [took 410.3575s]
|
||||
06/11/23 12:19:03| INFO bin_cc finished [took 396.9482s]
|
||||
06/11/23 12:20:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:20:41| INFO bin_sld_gsq finished [took 524.4318s]
|
||||
06/11/23 12:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00784) [took 546.2730s]
|
||||
06/11/23 12:22:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 640.2364s]
|
||||
06/11/23 12:23:20| INFO mul_sld_gs finished [took 683.6191s]
|
||||
06/11/23 12:24:29| INFO bin_pacc_gs finished [took 732.6258s]
|
||||
06/11/23 12:27:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 948.8111s]
|
||||
06/11/23 12:30:43| INFO bin_sld_gs finished [took 1128.0644s]
|
||||
06/11/23 12:30:43| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 1132.7995s]
|
||||
06/11/23 12:30:43| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 12:33:12| INFO mul_sld finished [took 146.3214s]
|
||||
06/11/23 12:33:24| INFO mul_cc finished [took 118.2992s]
|
||||
06/11/23 12:33:26| INFO doc_feat finished [took 96.3414s]
|
||||
06/11/23 12:33:36| INFO atc_ne finished [took 108.2657s]
|
||||
06/11/23 12:33:37| INFO mulne_pacc finished [took 155.4759s]
|
||||
06/11/23 12:33:39| INFO atc_mc finished [took 119.0950s]
|
||||
06/11/23 12:33:39| INFO mul_pacc finished [took 166.1039s]
|
||||
06/11/23 12:33:40| INFO ref finished [took 122.3921s]
|
||||
06/11/23 12:33:40| INFO mulmc_pacc finished [took 164.5722s]
|
||||
06/11/23 12:33:43| INFO kfcv finished [took 131.6124s]
|
||||
06/11/23 12:34:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00857) [took 188.0301s]
|
||||
06/11/23 12:35:45| INFO mul_pacc_gs finished [took 269.4655s]
|
||||
06/11/23 12:37:47| INFO binne_pacc finished [took 409.7038s]
|
||||
06/11/23 12:37:47| INFO bin_sld finished [took 421.4590s]
|
||||
06/11/23 12:37:55| INFO bin_pacc finished [took 423.8805s]
|
||||
06/11/23 12:37:57| INFO binmc_pacc finished [took 422.8180s]
|
||||
06/11/23 12:38:01| INFO bin_cc finished [took 400.2199s]
|
||||
06/11/23 12:39:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:39:41| INFO bin_sld_gsq finished [took 531.7360s]
|
||||
06/11/23 12:40:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.6726s]
|
||||
06/11/23 12:41:35| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 646.0507s]
|
||||
06/11/23 12:42:19| INFO mul_sld_gs finished [took 690.7431s]
|
||||
06/11/23 12:43:25| INFO bin_pacc_gs finished [took 737.2287s]
|
||||
06/11/23 12:47:07| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 979.3211s]
|
||||
06/11/23 12:50:07| INFO bin_sld_gs finished [took 1159.4207s]
|
||||
06/11/23 12:50:07| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1163.9370s]
|
||||
06/11/23 12:50:07| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 12:52:34| INFO doc_feat finished [took 79.3857s]
|
||||
06/11/23 12:52:39| INFO mul_pacc finished [took 143.2358s]
|
||||
06/11/23 12:52:49| INFO mul_sld finished [took 159.6160s]
|
||||
06/11/23 12:52:58| INFO kfcv finished [took 121.1756s]
|
||||
06/11/23 12:53:07| INFO mulmc_pacc finished [took 167.6154s]
|
||||
06/11/23 12:53:09| INFO atc_ne finished [took 115.9704s]
|
||||
06/11/23 12:53:11| INFO ref finished [took 127.9906s]
|
||||
06/11/23 12:53:17| INFO atc_mc finished [took 129.9605s]
|
||||
06/11/23 12:53:19| INFO mulne_pacc finished [took 166.1444s]
|
||||
06/11/23 12:53:21| INFO mul_cc finished [took 152.0451s]
|
||||
06/11/23 12:53:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.1015s]
|
||||
06/11/23 12:55:03| INFO mul_pacc_gs finished [took 261.6088s]
|
||||
06/11/23 12:57:20| INFO binmc_pacc finished [took 422.6680s]
|
||||
06/11/23 12:57:23| INFO bin_sld finished [took 434.1109s]
|
||||
06/11/23 12:57:26| INFO bin_pacc finished [took 431.1893s]
|
||||
06/11/23 12:57:28| INFO binne_pacc finished [took 427.7980s]
|
||||
06/11/23 12:57:29| INFO bin_cc finished [took 402.6463s]
|
||||
06/11/23 12:58:43| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:59:20| INFO bin_sld_gsq finished [took 546.8013s]
|
||||
06/11/23 12:59:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00858) [took 550.8127s]
|
||||
06/11/23 13:01:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 652.8483s]
|
||||
06/11/23 13:01:47| INFO mul_sld_gs finished [took 695.7927s]
|
||||
06/11/23 13:02:56| INFO bin_pacc_gs finished [took 739.4380s]
|
||||
06/11/23 13:06:49| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 999.0699s]
|
||||
06/11/23 13:09:50| INFO bin_sld_gs finished [took 1179.8181s]
|
||||
06/11/23 13:09:50| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1183.4124s]
|
||||
06/11/23 13:09:50| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 13:12:34| INFO doc_feat finished [took 88.8963s]
|
||||
06/11/23 13:12:43| INFO mul_sld finished [took 169.3932s]
|
||||
06/11/23 13:12:47| INFO mul_pacc finished [took 166.5633s]
|
||||
06/11/23 13:12:50| INFO kfcv finished [took 134.2527s]
|
||||
06/11/23 13:12:58| INFO ref finished [took 128.7367s]
|
||||
06/11/23 13:12:59| INFO mulne_pacc finished [took 161.0902s]
|
||||
06/11/23 13:13:00| INFO mulmc_pacc finished [took 176.8006s]
|
||||
06/11/23 13:13:01| INFO atc_mc finished [took 129.5173s]
|
||||
06/11/23 13:13:06| INFO atc_ne finished [took 122.8886s]
|
||||
06/11/23 13:13:16| INFO mul_cc finished [took 152.5218s]
|
||||
06/11/23 13:13:34| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00774) [took 183.0928s]
|
||||
06/11/23 13:14:57| INFO mul_pacc_gs finished [took 266.4369s]
|
||||
06/11/23 13:17:06| INFO bin_pacc finished [took 427.3693s]
|
||||
06/11/23 13:17:08| INFO binmc_pacc finished [took 426.6359s]
|
||||
06/11/23 13:17:14| INFO bin_sld finished [took 441.7834s]
|
||||
06/11/23 13:17:20| INFO binne_pacc finished [took 435.6569s]
|
||||
06/11/23 13:17:22| INFO bin_cc finished [took 412.7263s]
|
||||
06/11/23 13:18:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 13:19:06| INFO bin_sld_gsq finished [took 549.0379s]
|
||||
06/11/23 13:19:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00709) [took 545.0306s]
|
||||
06/11/23 13:20:41| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 645.5669s]
|
||||
06/11/23 13:21:25| INFO mul_sld_gs finished [took 689.4814s]
|
||||
06/11/23 13:22:32| INFO bin_pacc_gs finished [took 730.0602s]
|
||||
06/11/23 13:26:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 985.8522s]
|
||||
06/11/23 13:29:21| INFO bin_sld_gs finished [took 1166.4200s]
|
||||
06/11/23 13:29:21| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 1170.8744s]
|
||||
06/11/23 13:29:21| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 13:31:52| INFO doc_feat finished [took 80.3058s]
|
||||
06/11/23 13:32:00| INFO mul_sld finished [took 153.1261s]
|
||||
06/11/23 13:32:00| INFO mul_pacc finished [took 148.0156s]
|
||||
06/11/23 13:32:13| INFO kfcv finished [took 122.2270s]
|
||||
06/11/23 13:32:13| INFO mulne_pacc finished [took 145.0130s]
|
||||
06/11/23 13:32:22| INFO ref finished [took 122.3525s]
|
||||
06/11/23 13:32:23| INFO atc_mc finished [took 120.2587s]
|
||||
06/11/23 13:32:23| INFO atc_ne finished [took 113.5667s]
|
||||
06/11/23 13:32:23| INFO mulmc_pacc finished [took 167.7106s]
|
||||
06/11/23 13:32:36| INFO mul_cc finished [took 143.6517s]
|
||||
06/11/23 13:33:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00802) [took 182.2049s]
|
||||
06/11/23 13:34:23| INFO mul_pacc_gs finished [took 261.0038s]
|
||||
06/11/23 13:36:19| INFO binmc_pacc finished [took 405.9199s]
|
||||
06/11/23 13:36:31| INFO bin_sld finished [took 426.3780s]
|
||||
06/11/23 13:36:32| INFO bin_pacc finished [took 420.2833s]
|
||||
06/11/23 13:36:34| INFO binne_pacc finished [took 417.2048s]
|
||||
06/11/23 13:36:42| INFO bin_cc finished [took 394.3524s]
|
||||
06/11/23 13:37:45| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 13:38:18| INFO bin_sld_gsq finished [took 528.6956s]
|
||||
06/11/23 13:38:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00707) [took 544.2769s]
|
||||
06/11/23 13:39:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 628.0656s]
|
||||
06/11/23 13:40:41| INFO mul_sld_gs finished [took 673.3968s]
|
||||
06/11/23 13:41:58| INFO bin_pacc_gs finished [took 730.5371s]
|
||||
06/11/23 13:45:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 960.1061s]
|
||||
06/11/23 13:48:28| INFO bin_sld_gs finished [took 1140.6073s]
|
||||
06/11/23 13:48:28| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1146.6395s]
|
||||
06/11/23 13:48:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 13:50:49| INFO mul_pacc finished [took 130.9408s]
|
||||
06/11/23 13:51:02| INFO doc_feat finished [took 86.2411s]
|
||||
06/11/23 13:51:07| INFO mul_sld finished [took 155.4513s]
|
||||
06/11/23 13:51:15| INFO atc_ne finished [took 101.0761s]
|
||||
06/11/23 13:51:20| INFO ref finished [took 121.3689s]
|
||||
06/11/23 13:51:20| INFO atc_mc finished [took 106.6415s]
|
||||
06/11/23 13:51:22| INFO mulmc_pacc finished [took 160.4221s]
|
||||
06/11/23 13:51:22| INFO mulne_pacc finished [took 150.1203s]
|
||||
06/11/23 13:51:25| INFO kfcv finished [took 127.5280s]
|
||||
06/11/23 13:51:35| INFO mul_cc finished [took 145.4437s]
|
||||
06/11/23 13:52:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00886) [took 182.0543s]
|
||||
06/11/23 13:53:23| INFO mul_pacc_gs finished [took 262.2496s]
|
||||
06/11/23 13:55:28| INFO bin_sld finished [took 417.7315s]
|
||||
06/11/23 13:55:30| INFO binmc_pacc finished [took 410.0114s]
|
||||
06/11/23 13:55:30| INFO bin_pacc finished [took 413.5912s]
|
||||
06/11/23 13:55:35| INFO binne_pacc finished [took 411.8241s]
|
||||
06/11/23 13:55:42| INFO bin_cc finished [took 396.5011s]
|
||||
06/11/23 13:56:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 13:57:22| INFO bin_sld_gsq finished [took 527.2507s]
|
||||
06/11/23 13:58:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00910) [took 547.7641s]
|
||||
06/11/23 13:59:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 634.8469s]
|
||||
06/11/23 13:59:54| INFO mul_sld_gs finished [took 680.2027s]
|
||||
06/11/23 14:01:07| INFO bin_pacc_gs finished [took 731.8655s]
|
||||
06/11/23 14:04:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 960.6861s]
|
||||
06/11/23 14:07:34| INFO bin_sld_gs finished [took 1141.7199s]
|
||||
06/11/23 14:07:34| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 1146.2680s]
|
||||
06/11/23 14:07:34| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 14:10:08| INFO mulmc_pacc finished [took 141.2266s]
|
||||
06/11/23 14:10:19| INFO atc_ne finished [took 101.4512s]
|
||||
06/11/23 14:10:20| INFO mul_sld finished [took 162.5808s]
|
||||
06/11/23 14:10:23| INFO mul_pacc finished [took 158.9068s]
|
||||
06/11/23 14:10:30| INFO kfcv finished [took 123.4790s]
|
||||
06/11/23 14:10:33| INFO mulne_pacc finished [took 158.4983s]
|
||||
06/11/23 14:10:33| INFO doc_feat finished [took 111.7987s]
|
||||
06/11/23 14:10:35| INFO ref finished [took 124.4184s]
|
||||
06/11/23 14:10:40| INFO atc_mc finished [took 126.3543s]
|
||||
06/11/23 14:10:40| INFO mul_cc finished [took 139.5958s]
|
||||
06/11/23 14:11:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.01309) [took 184.0645s]
|
||||
06/11/23 14:12:44| INFO mul_pacc_gs finished [took 272.5404s]
|
||||
06/11/23 14:14:32| INFO binmc_pacc finished [took 406.3609s]
|
||||
06/11/23 14:14:38| INFO bin_pacc finished [took 414.8972s]
|
||||
06/11/23 14:14:43| INFO binne_pacc finished [took 414.4123s]
|
||||
06/11/23 14:14:51| INFO bin_cc finished [took 395.5254s]
|
||||
06/11/23 14:14:55| INFO bin_sld finished [took 437.7681s]
|
||||
06/11/23 14:15:58| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 14:16:33| INFO bin_sld_gsq finished [took 532.4040s]
|
||||
06/11/23 14:16:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00812) [took 536.4746s]
|
||||
06/11/23 14:18:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 636.4067s]
|
||||
06/11/23 14:19:00| INFO mul_sld_gs finished [took 680.2467s]
|
||||
06/11/23 14:20:01| INFO bin_pacc_gs finished [took 720.9205s]
|
||||
06/11/23 14:23:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 954.4487s]
|
||||
06/11/23 14:26:41| INFO bin_sld_gs finished [took 1142.3328s]
|
||||
06/11/23 14:26:41| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 1146.7713s]
|
||||
06/11/23 14:26:41| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 14:29:04| INFO mul_pacc finished [took 133.1736s]
|
||||
06/11/23 14:29:07| INFO ref finished [took 87.1594s]
|
||||
06/11/23 14:29:16| INFO doc_feat finished [took 83.8190s]
|
||||
06/11/23 14:29:21| INFO mulmc_pacc finished [took 147.5202s]
|
||||
06/11/23 14:29:22| INFO atc_mc finished [took 99.1039s]
|
||||
06/11/23 14:29:23| INFO kfcv finished [took 109.5348s]
|
||||
06/11/23 14:29:27| INFO mulne_pacc finished [took 148.1672s]
|
||||
06/11/23 14:29:33| INFO atc_ne finished [took 101.4673s]
|
||||
06/11/23 14:29:36| INFO mul_cc finished [took 126.0447s]
|
||||
06/11/23 14:29:42| INFO mul_sld finished [took 177.5880s]
|
||||
06/11/23 14:30:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01497) [took 175.1432s]
|
||||
06/11/23 14:31:33| INFO mul_pacc_gs finished [took 252.3399s]
|
||||
06/11/23 14:33:34| INFO binmc_pacc finished [took 401.7891s]
|
||||
06/11/23 14:33:35| INFO binne_pacc finished [took 400.4138s]
|
||||
06/11/23 14:33:36| INFO bin_pacc finished [took 406.7598s]
|
||||
06/11/23 14:33:48| INFO bin_cc finished [took 378.7595s]
|
||||
06/11/23 14:33:48| INFO bin_sld finished [took 423.7366s]
|
||||
06/11/23 14:34:47| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 14:35:26| INFO bin_sld_gsq finished [took 518.8996s]
|
||||
06/11/23 14:36:13| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00880) [took 539.3992s]
|
||||
06/11/23 14:37:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 622.0419s]
|
||||
06/11/23 14:37:53| INFO mul_sld_gs finished [took 666.0058s]
|
||||
06/11/23 14:39:16| INFO bin_pacc_gs finished [took 722.5231s]
|
||||
06/11/23 14:42:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 929.3464s]
|
||||
06/11/23 14:45:14| INFO bin_sld_gs finished [took 1108.7356s]
|
||||
06/11/23 14:45:14| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 1113.2364s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
07/11/23 01:05:25| INFO dataset rcv1_CCAT_9prevs
|
||||
07/11/23 01:05:30| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:06:23| INFO ref finished [took 48.3560s]
|
||||
07/11/23 01:06:29| INFO atc_mc finished [took 52.9929s]
|
||||
07/11/23 01:06:30| INFO atc_ne finished [took 53.3908s]
|
||||
07/11/23 01:07:06| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
07/11/23 01:11:38| INFO mul_sld_gsq finished [took 364.0698s]
|
||||
07/11/23 01:13:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 499.4945s]
|
||||
07/11/23 01:14:34| INFO mul_sld_gs finished [took 542.6047s]
|
||||
07/11/23 01:18:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 750.8663s]
|
||||
07/11/23 01:21:01| INFO bin_sld_gs finished [took 930.1356s]
|
||||
07/11/23 01:21:01| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 931.4321s]
|
||||
07/11/23 01:21:01| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:22:02| INFO ref finished [took 55.2212s]
|
||||
07/11/23 01:22:07| INFO atc_mc finished [took 59.3890s]
|
||||
07/11/23 01:22:09| INFO atc_ne finished [took 59.7388s]
|
||||
07/11/23 01:27:21| INFO mul_sld_gsq finished [took 375.2352s]
|
||||
07/11/23 01:27:24| INFO bin_sld_gsq finished [took 379.6159s]
|
||||
07/11/23 01:29:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 502.0302s]
|
||||
07/11/23 01:30:08| INFO mul_sld_gs finished [took 545.0285s]
|
||||
07/11/23 01:34:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 802.3620s]
|
||||
07/11/23 01:37:25| INFO bin_sld_gs finished [took 982.3260s]
|
||||
07/11/23 01:37:25| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 983.7236s]
|
||||
07/11/23 01:37:25| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:38:20| INFO ref finished [took 49.9803s]
|
||||
07/11/23 01:38:25| INFO atc_mc finished [took 53.3765s]
|
||||
07/11/23 01:38:26| INFO atc_ne finished [took 53.8925s]
|
||||
07/11/23 01:43:41| INFO mul_sld_gsq finished [took 372.2608s]
|
||||
07/11/23 01:43:45| INFO bin_sld_gsq finished [took 377.3380s]
|
||||
07/11/23 01:45:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 497.5768s]
|
||||
07/11/23 01:46:28| INFO mul_sld_gs finished [took 540.8267s]
|
||||
07/11/23 01:51:09| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 822.2849s]
|
||||
07/11/23 01:54:10| INFO bin_sld_gs finished [took 1003.7804s]
|
||||
07/11/23 01:54:10| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1005.2506s]
|
||||
07/11/23 01:54:10| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:55:05| INFO ref finished [took 49.8884s]
|
||||
07/11/23 01:55:09| INFO atc_mc finished [took 53.3594s]
|
||||
07/11/23 01:55:10| INFO atc_ne finished [took 53.5162s]
|
||||
07/11/23 02:00:25| INFO mul_sld_gsq finished [took 371.4460s]
|
||||
07/11/23 02:00:41| INFO bin_sld_gsq finished [took 387.6183s]
|
||||
07/11/23 02:02:30| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 498.0096s]
|
||||
07/11/23 02:03:11| INFO mul_sld_gs finished [took 539.1531s]
|
||||
07/11/23 02:07:53| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 821.8730s]
|
||||
07/11/23 02:10:52| INFO bin_sld_gs finished [took 1001.0803s]
|
||||
07/11/23 02:10:52| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1002.3085s]
|
||||
07/11/23 02:10:52| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 02:11:44| INFO ref finished [took 47.2218s]
|
||||
07/11/23 02:11:48| INFO atc_mc finished [took 49.6349s]
|
||||
07/11/23 02:11:50| INFO atc_ne finished [took 50.9082s]
|
||||
07/11/23 02:16:51| INFO mul_sld_gsq finished [took 354.3706s]
|
||||
07/11/23 02:17:11| INFO bin_sld_gsq finished [took 376.0124s]
|
||||
07/11/23 02:18:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 476.0587s]
|
||||
07/11/23 02:19:33| INFO mul_sld_gs finished [took 518.5692s]
|
||||
07/11/23 02:24:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 803.4978s]
|
||||
07/11/23 02:27:16| INFO bin_sld_gs finished [took 982.4395s]
|
||||
07/11/23 02:27:16| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 983.7838s]
|
||||
07/11/23 02:27:16| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 02:28:08| INFO ref finished [took 46.6191s]
|
||||
07/11/23 02:28:13| INFO atc_mc finished [took 50.3543s]
|
||||
07/11/23 02:28:15| INFO atc_ne finished [took 51.6601s]
|
||||
07/11/23 02:33:15| INFO mul_sld_gsq finished [took 354.6014s]
|
||||
07/11/23 02:33:34| INFO bin_sld_gsq finished [took 374.7872s]
|
||||
07/11/23 02:35:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 475.9302s]
|
||||
07/11/23 02:35:57| INFO mul_sld_gs finished [took 518.5425s]
|
||||
07/11/23 02:40:20| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 782.7268s]
|
||||
07/11/23 02:43:18| INFO bin_sld_gs finished [took 960.6334s]
|
||||
07/11/23 02:43:18| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 961.9030s]
|
||||
07/11/23 02:43:18| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 02:44:10| INFO ref finished [took 47.1234s]
|
||||
07/11/23 02:44:14| INFO atc_mc finished [took 49.9871s]
|
||||
07/11/23 02:44:16| INFO atc_ne finished [took 50.9160s]
|
||||
07/11/23 02:49:19| INFO mul_sld_gsq finished [took 357.0613s]
|
||||
07/11/23 02:49:30| INFO bin_sld_gsq finished [took 368.8000s]
|
||||
07/11/23 02:51:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 475.7332s]
|
||||
07/11/23 02:51:59| INFO mul_sld_gs finished [took 518.6671s]
|
||||
07/11/23 02:56:28| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 788.7117s]
|
||||
07/11/23 02:59:28| INFO bin_sld_gs finished [took 968.7653s]
|
||||
07/11/23 02:59:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 970.1516s]
|
||||
07/11/23 02:59:28| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 03:00:20| INFO ref finished [took 46.9898s]
|
||||
07/11/23 03:00:24| INFO atc_mc finished [took 49.8768s]
|
||||
07/11/23 03:00:25| INFO atc_ne finished [took 49.6324s]
|
||||
07/11/23 03:05:23| INFO mul_sld_gsq finished [took 350.7932s]
|
||||
07/11/23 03:05:32| INFO bin_sld_gsq finished [took 360.8665s]
|
||||
07/11/23 03:07:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 474.6581s]
|
||||
07/11/23 03:08:07| INFO mul_sld_gs finished [took 516.4890s]
|
||||
07/11/23 03:12:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 774.9140s]
|
||||
07/11/23 03:15:29| INFO bin_sld_gs finished [took 959.3579s]
|
||||
07/11/23 03:15:29| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 960.6992s]
|
||||
07/11/23 03:15:29| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 03:16:21| INFO ref finished [took 47.3281s]
|
||||
07/11/23 03:16:25| INFO atc_mc finished [took 49.8016s]
|
||||
07/11/23 03:16:28| INFO atc_ne finished [took 51.2288s]
|
||||
07/11/23 03:21:16| INFO mul_sld_gsq finished [took 343.2861s]
|
||||
07/11/23 03:21:22| INFO bin_sld_gsq finished [took 349.6065s]
|
||||
07/11/23 03:23:20| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 468.7910s]
|
||||
07/11/23 03:24:01| INFO mul_sld_gs finished [took 509.9001s]
|
||||
07/11/23 03:28:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 752.8185s]
|
||||
07/11/23 03:31:01| INFO bin_sld_gs finished [took 930.3934s]
|
||||
07/11/23 03:31:01| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 931.7055s]
|
||||
06/11/23 05:14:48| INFO dataset rcv1_CCAT_9prevs
|
||||
06/11/23 05:14:53| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:15:55| INFO ref finished [took 48.0242s]
|
||||
06/11/23 05:16:01| INFO atc_mc finished [took 51.7851s]
|
||||
06/11/23 05:16:04| INFO mul_pacc finished [took 58.4704s]
|
||||
06/11/23 05:16:04| INFO mulne_sld finished [took 62.7354s]
|
||||
06/11/23 05:16:04| INFO mulmc_sld finished [took 66.2593s]
|
||||
06/11/23 05:16:14| INFO mul_sld finished [took 78.2483s]
|
||||
06/11/23 05:18:40| INFO bin_pacc finished [took 217.0012s]
|
||||
06/11/23 05:18:43| INFO bin_sld finished [took 227.8835s]
|
||||
06/11/23 05:18:43| INFO binne_sld finished [took 223.2764s]
|
||||
06/11/23 05:18:44| INFO binmc_sld finished [took 226.7324s]
|
||||
06/11/23 05:18:44| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 230.5906s]
|
||||
06/11/23 05:18:44| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:19:44| INFO ref finished [took 49.5147s]
|
||||
06/11/23 05:19:51| INFO atc_mc finished [took 54.8022s]
|
||||
06/11/23 05:19:53| INFO mul_pacc finished [took 60.3260s]
|
||||
06/11/23 05:19:55| INFO mulmc_sld finished [took 67.0280s]
|
||||
06/11/23 05:19:56| INFO mul_sld finished [took 70.4092s]
|
||||
06/11/23 05:19:58| INFO mulne_sld finished [took 67.3468s]
|
||||
06/11/23 05:22:30| INFO bin_sld finished [took 224.7344s]
|
||||
06/11/23 05:22:30| INFO bin_pacc finished [took 218.3044s]
|
||||
06/11/23 05:22:30| INFO binmc_sld finished [took 223.3607s]
|
||||
06/11/23 05:22:33| INFO binne_sld finished [took 223.6042s]
|
||||
06/11/23 05:22:33| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 229.0745s]
|
||||
06/11/23 05:22:33| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:23:32| INFO ref finished [took 48.1565s]
|
||||
06/11/23 05:23:37| INFO atc_mc finished [took 52.1124s]
|
||||
06/11/23 05:23:40| INFO mul_pacc finished [took 58.0112s]
|
||||
06/11/23 05:23:40| INFO mul_sld finished [took 65.2727s]
|
||||
06/11/23 05:23:42| INFO mulmc_sld finished [took 64.5943s]
|
||||
06/11/23 05:23:43| INFO mulne_sld finished [took 63.9053s]
|
||||
06/11/23 05:26:13| INFO bin_sld finished [took 218.6511s]
|
||||
06/11/23 05:26:16| INFO bin_pacc finished [took 215.1485s]
|
||||
06/11/23 05:26:17| INFO binne_sld finished [took 218.6855s]
|
||||
06/11/23 05:26:17| INFO binmc_sld finished [took 221.2605s]
|
||||
06/11/23 05:26:17| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 224.5608s]
|
||||
06/11/23 05:26:17| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:27:15| INFO ref finished [took 48.2181s]
|
||||
06/11/23 05:27:21| INFO atc_mc finished [took 52.3420s]
|
||||
06/11/23 05:27:23| INFO mul_pacc finished [took 57.1950s]
|
||||
06/11/23 05:27:24| INFO mul_sld finished [took 64.4722s]
|
||||
06/11/23 05:27:26| INFO mulmc_sld finished [took 64.1870s]
|
||||
06/11/23 05:27:27| INFO mulne_sld finished [took 63.7407s]
|
||||
06/11/23 05:29:52| INFO bin_sld finished [took 213.1913s]
|
||||
06/11/23 05:29:53| INFO bin_pacc finished [took 208.1322s]
|
||||
06/11/23 05:29:53| INFO binmc_sld finished [took 212.6473s]
|
||||
06/11/23 05:29:57| INFO binne_sld finished [took 214.5243s]
|
||||
06/11/23 05:29:57| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 219.5765s]
|
||||
06/11/23 05:29:57| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:30:55| INFO ref finished [took 47.7289s]
|
||||
06/11/23 05:31:01| INFO atc_mc finished [took 52.1531s]
|
||||
06/11/23 05:31:03| INFO mul_pacc finished [took 57.3804s]
|
||||
06/11/23 05:31:06| INFO mul_sld finished [took 66.9237s]
|
||||
06/11/23 05:31:06| INFO mulmc_sld finished [took 65.3230s]
|
||||
06/11/23 05:31:09| INFO mulne_sld finished [took 65.6645s]
|
||||
06/11/23 05:33:33| INFO bin_sld finished [took 214.3242s]
|
||||
06/11/23 05:33:34| INFO bin_pacc finished [took 209.3862s]
|
||||
06/11/23 05:33:35| INFO binmc_sld finished [took 214.4687s]
|
||||
06/11/23 05:33:37| INFO binne_sld finished [took 214.7267s]
|
||||
06/11/23 05:33:37| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 220.0212s]
|
||||
06/11/23 05:33:37| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:34:35| INFO ref finished [took 48.0021s]
|
||||
06/11/23 05:34:41| INFO atc_mc finished [took 52.2171s]
|
||||
06/11/23 05:34:43| INFO mul_pacc finished [took 57.2348s]
|
||||
06/11/23 05:34:46| INFO mul_sld finished [took 67.0899s]
|
||||
06/11/23 05:34:47| INFO mulmc_sld finished [took 66.1078s]
|
||||
06/11/23 05:34:49| INFO mulne_sld finished [took 66.0237s]
|
||||
06/11/23 05:37:13| INFO bin_sld finished [took 214.9942s]
|
||||
06/11/23 05:37:13| INFO binmc_sld finished [took 213.1574s]
|
||||
06/11/23 05:37:14| INFO bin_pacc finished [took 209.1347s]
|
||||
06/11/23 05:37:17| INFO binne_sld finished [took 214.9703s]
|
||||
06/11/23 05:37:17| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 220.1235s]
|
||||
06/11/23 05:37:17| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:38:15| INFO ref finished [took 47.8227s]
|
||||
06/11/23 05:38:20| INFO atc_mc finished [took 51.9364s]
|
||||
06/11/23 05:38:23| INFO mul_pacc finished [took 56.9053s]
|
||||
06/11/23 05:38:27| INFO mul_sld finished [took 67.4535s]
|
||||
06/11/23 05:38:27| INFO mulmc_sld finished [took 65.5956s]
|
||||
06/11/23 05:38:30| INFO mulne_sld finished [took 66.0476s]
|
||||
06/11/23 05:40:55| INFO bin_pacc finished [took 210.0633s]
|
||||
06/11/23 05:40:56| INFO binmc_sld finished [took 215.3452s]
|
||||
06/11/23 05:40:56| INFO bin_sld finished [took 217.8091s]
|
||||
06/11/23 05:40:59| INFO binne_sld finished [took 216.8970s]
|
||||
06/11/23 05:40:59| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 222.2971s]
|
||||
06/11/23 05:40:59| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:41:57| INFO ref finished [took 47.6970s]
|
||||
06/11/23 05:42:03| INFO atc_mc finished [took 52.0893s]
|
||||
06/11/23 05:42:05| INFO mul_pacc finished [took 56.6428s]
|
||||
06/11/23 05:42:09| INFO mul_sld finished [took 66.8810s]
|
||||
06/11/23 05:42:09| INFO mulmc_sld finished [took 65.8427s]
|
||||
06/11/23 05:42:11| INFO mulne_sld finished [took 64.8594s]
|
||||
06/11/23 05:44:36| INFO bin_pacc finished [took 208.7884s]
|
||||
06/11/23 05:44:38| INFO bin_sld finished [took 216.6052s]
|
||||
06/11/23 05:44:38| INFO binmc_sld finished [took 215.5486s]
|
||||
06/11/23 05:44:43| INFO binne_sld finished [took 217.9926s]
|
||||
06/11/23 05:44:43| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 223.2270s]
|
||||
06/11/23 05:44:43| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 05:45:40| INFO ref finished [took 48.0710s]
|
||||
06/11/23 05:45:46| INFO atc_mc finished [took 52.0992s]
|
||||
06/11/23 05:45:48| INFO mul_pacc finished [took 56.6568s]
|
||||
06/11/23 05:45:49| INFO mulmc_sld finished [took 61.7314s]
|
||||
06/11/23 05:45:52| INFO mulne_sld finished [took 62.7505s]
|
||||
06/11/23 05:45:59| INFO mul_sld finished [took 73.7681s]
|
||||
06/11/23 05:48:18| INFO bin_pacc finished [took 208.2267s]
|
||||
06/11/23 05:48:23| INFO bin_sld finished [took 218.9333s]
|
||||
06/11/23 05:48:24| INFO binmc_sld finished [took 218.0032s]
|
||||
06/11/23 05:48:27| INFO binne_sld finished [took 219.2450s]
|
||||
06/11/23 05:48:27| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 224.3446s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 11:53:50| INFO dataset rcv1_CCAT_9prevs
|
||||
06/11/23 11:53:56| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 11:56:45| INFO doc_feat finished [took 83.7957s]
|
||||
06/11/23 11:56:58| INFO mulne_pacc finished [took 146.6577s]
|
||||
06/11/23 11:57:03| INFO ref finished [took 120.2665s]
|
||||
06/11/23 11:57:05| INFO mul_pacc finished [took 169.5909s]
|
||||
06/11/23 11:57:07| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 11:57:08| INFO kfcv finished [took 130.0948s]
|
||||
06/11/23 11:57:13| INFO mulmc_pacc finished [took 173.0431s]
|
||||
06/11/23 11:57:16| INFO atc_mc finished [took 125.2363s]
|
||||
06/11/23 11:57:17| INFO mul_sld finished [took 199.1179s]
|
||||
06/11/23 11:57:18| INFO mul_cc finished [took 148.2203s]
|
||||
06/11/23 11:57:20| INFO atc_ne finished [took 121.9570s]
|
||||
06/11/23 11:57:39| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00899) [took 176.8809s]
|
||||
06/11/23 11:58:48| INFO mul_pacc_gs finished [took 245.7641s]
|
||||
06/11/23 12:00:56| INFO bin_pacc finished [took 409.8967s]
|
||||
06/11/23 12:01:03| INFO bin_sld finished [took 426.0031s]
|
||||
06/11/23 12:01:09| INFO binmc_pacc finished [took 412.9057s]
|
||||
06/11/23 12:01:13| INFO bin_cc finished [took 389.4719s]
|
||||
06/11/23 12:01:14| INFO binne_pacc finished [took 411.1276s]
|
||||
06/11/23 12:02:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:03:18| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00719) [took 523.4665s]
|
||||
06/11/23 12:04:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 643.3372s]
|
||||
06/11/23 12:05:27| INFO mul_sld_gs finished [took 686.5912s]
|
||||
06/11/23 12:06:25| INFO bin_pacc_gs finished [took 710.5248s]
|
||||
06/11/23 12:08:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 892.3454s]
|
||||
06/11/23 12:11:50| INFO bin_sld_gs finished [took 1070.2847s]
|
||||
06/11/23 12:11:50| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 1073.7689s]
|
||||
06/11/23 12:11:50| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 12:14:15| INFO doc_feat finished [took 80.2198s]
|
||||
06/11/23 12:14:27| INFO ref finished [took 106.1446s]
|
||||
06/11/23 12:14:36| INFO mul_pacc finished [took 155.8715s]
|
||||
06/11/23 12:14:37| INFO mul_sld finished [took 162.7857s]
|
||||
06/11/23 12:14:47| INFO kfcv finished [took 132.1178s]
|
||||
06/11/23 12:14:55| INFO atc_mc finished [took 127.9109s]
|
||||
06/11/23 12:14:57| INFO atc_ne finished [took 121.6128s]
|
||||
06/11/23 12:14:58| INFO mulmc_pacc finished [took 173.9023s]
|
||||
06/11/23 12:14:58| INFO mulne_pacc finished [took 167.2920s]
|
||||
06/11/23 12:14:59| INFO mul_cc finished [took 147.7428s]
|
||||
06/11/23 12:15:28| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00931) [took 186.6087s]
|
||||
06/11/23 12:16:44| INFO mul_pacc_gs finished [took 261.9352s]
|
||||
06/11/23 12:18:49| INFO binmc_pacc finished [took 407.0394s]
|
||||
06/11/23 12:18:50| INFO bin_pacc finished [took 410.4620s]
|
||||
06/11/23 12:18:55| INFO bin_sld finished [took 422.8949s]
|
||||
06/11/23 12:19:01| INFO binne_pacc finished [took 410.3575s]
|
||||
06/11/23 12:19:03| INFO bin_cc finished [took 396.9482s]
|
||||
06/11/23 12:20:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:20:41| INFO bin_sld_gsq finished [took 524.4318s]
|
||||
06/11/23 12:21:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00784) [took 546.2730s]
|
||||
06/11/23 12:22:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 640.2364s]
|
||||
06/11/23 12:23:20| INFO mul_sld_gs finished [took 683.6191s]
|
||||
06/11/23 12:24:29| INFO bin_pacc_gs finished [took 732.6258s]
|
||||
06/11/23 12:27:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 948.8111s]
|
||||
06/11/23 12:30:43| INFO bin_sld_gs finished [took 1128.0644s]
|
||||
06/11/23 12:30:43| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 1132.7995s]
|
||||
06/11/23 12:30:43| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 12:33:12| INFO mul_sld finished [took 146.3214s]
|
||||
06/11/23 12:33:24| INFO mul_cc finished [took 118.2992s]
|
||||
06/11/23 12:33:26| INFO doc_feat finished [took 96.3414s]
|
||||
06/11/23 12:33:36| INFO atc_ne finished [took 108.2657s]
|
||||
06/11/23 12:33:37| INFO mulne_pacc finished [took 155.4759s]
|
||||
06/11/23 12:33:39| INFO atc_mc finished [took 119.0950s]
|
||||
06/11/23 12:33:39| INFO mul_pacc finished [took 166.1039s]
|
||||
06/11/23 12:33:40| INFO ref finished [took 122.3921s]
|
||||
06/11/23 12:33:40| INFO mulmc_pacc finished [took 164.5722s]
|
||||
06/11/23 12:33:43| INFO kfcv finished [took 131.6124s]
|
||||
06/11/23 12:34:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00857) [took 188.0301s]
|
||||
06/11/23 12:35:45| INFO mul_pacc_gs finished [took 269.4655s]
|
||||
06/11/23 12:37:47| INFO binne_pacc finished [took 409.7038s]
|
||||
06/11/23 12:37:47| INFO bin_sld finished [took 421.4590s]
|
||||
06/11/23 12:37:55| INFO bin_pacc finished [took 423.8805s]
|
||||
06/11/23 12:37:57| INFO binmc_pacc finished [took 422.8180s]
|
||||
06/11/23 12:38:01| INFO bin_cc finished [took 400.2199s]
|
||||
06/11/23 12:39:14| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:39:41| INFO bin_sld_gsq finished [took 531.7360s]
|
||||
06/11/23 12:40:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.6726s]
|
||||
06/11/23 12:41:35| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 646.0507s]
|
||||
06/11/23 12:42:19| INFO mul_sld_gs finished [took 690.7431s]
|
||||
06/11/23 12:43:25| INFO bin_pacc_gs finished [took 737.2287s]
|
||||
06/11/23 12:47:07| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 979.3211s]
|
||||
06/11/23 12:50:07| INFO bin_sld_gs finished [took 1159.4207s]
|
||||
06/11/23 12:50:07| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1163.9370s]
|
||||
06/11/23 12:50:07| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 12:52:34| INFO doc_feat finished [took 79.3857s]
|
||||
06/11/23 12:52:39| INFO mul_pacc finished [took 143.2358s]
|
||||
06/11/23 12:52:49| INFO mul_sld finished [took 159.6160s]
|
||||
06/11/23 12:52:58| INFO kfcv finished [took 121.1756s]
|
||||
06/11/23 12:53:07| INFO mulmc_pacc finished [took 167.6154s]
|
||||
06/11/23 12:53:09| INFO atc_ne finished [took 115.9704s]
|
||||
06/11/23 12:53:11| INFO ref finished [took 127.9906s]
|
||||
06/11/23 12:53:17| INFO atc_mc finished [took 129.9605s]
|
||||
06/11/23 12:53:19| INFO mulne_pacc finished [took 166.1444s]
|
||||
06/11/23 12:53:21| INFO mul_cc finished [took 152.0451s]
|
||||
06/11/23 12:53:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.1015s]
|
||||
06/11/23 12:55:03| INFO mul_pacc_gs finished [took 261.6088s]
|
||||
06/11/23 12:57:20| INFO binmc_pacc finished [took 422.6680s]
|
||||
06/11/23 12:57:23| INFO bin_sld finished [took 434.1109s]
|
||||
06/11/23 12:57:26| INFO bin_pacc finished [took 431.1893s]
|
||||
06/11/23 12:57:28| INFO binne_pacc finished [took 427.7980s]
|
||||
06/11/23 12:57:29| INFO bin_cc finished [took 402.6463s]
|
||||
06/11/23 12:58:43| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 12:59:20| INFO bin_sld_gsq finished [took 546.8013s]
|
||||
06/11/23 12:59:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00858) [took 550.8127s]
|
||||
06/11/23 13:01:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 652.8483s]
|
||||
06/11/23 13:01:47| INFO mul_sld_gs finished [took 695.7927s]
|
||||
06/11/23 13:02:56| INFO bin_pacc_gs finished [took 739.4380s]
|
||||
06/11/23 13:06:49| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 999.0699s]
|
||||
06/11/23 13:09:50| INFO bin_sld_gs finished [took 1179.8181s]
|
||||
06/11/23 13:09:50| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1183.4124s]
|
||||
06/11/23 13:09:50| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 13:12:34| INFO doc_feat finished [took 88.8963s]
|
||||
06/11/23 13:12:43| INFO mul_sld finished [took 169.3932s]
|
||||
06/11/23 13:12:47| INFO mul_pacc finished [took 166.5633s]
|
||||
06/11/23 13:12:50| INFO kfcv finished [took 134.2527s]
|
||||
06/11/23 13:12:58| INFO ref finished [took 128.7367s]
|
||||
06/11/23 13:12:59| INFO mulne_pacc finished [took 161.0902s]
|
||||
06/11/23 13:13:00| INFO mulmc_pacc finished [took 176.8006s]
|
||||
06/11/23 13:13:01| INFO atc_mc finished [took 129.5173s]
|
||||
06/11/23 13:13:06| INFO atc_ne finished [took 122.8886s]
|
||||
06/11/23 13:13:16| INFO mul_cc finished [took 152.5218s]
|
||||
06/11/23 13:13:34| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.00774) [took 183.0928s]
|
||||
06/11/23 13:14:57| INFO mul_pacc_gs finished [took 266.4369s]
|
||||
06/11/23 13:17:06| INFO bin_pacc finished [took 427.3693s]
|
||||
06/11/23 13:17:08| INFO binmc_pacc finished [took 426.6359s]
|
||||
06/11/23 13:17:14| INFO bin_sld finished [took 441.7834s]
|
||||
06/11/23 13:17:20| INFO binne_pacc finished [took 435.6569s]
|
||||
06/11/23 13:17:22| INFO bin_cc finished [took 412.7263s]
|
||||
06/11/23 13:18:20| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 13:19:06| INFO bin_sld_gsq finished [took 549.0379s]
|
||||
06/11/23 13:19:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00709) [took 545.0306s]
|
||||
06/11/23 13:20:41| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 645.5669s]
|
||||
06/11/23 13:21:25| INFO mul_sld_gs finished [took 689.4814s]
|
||||
06/11/23 13:22:32| INFO bin_pacc_gs finished [took 730.0602s]
|
||||
06/11/23 13:26:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 985.8522s]
|
||||
06/11/23 13:29:21| INFO bin_sld_gs finished [took 1166.4200s]
|
||||
06/11/23 13:29:21| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 1170.8744s]
|
||||
06/11/23 13:29:21| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 13:31:52| INFO doc_feat finished [took 80.3058s]
|
||||
06/11/23 13:32:00| INFO mul_sld finished [took 153.1261s]
|
||||
06/11/23 13:32:00| INFO mul_pacc finished [took 148.0156s]
|
||||
06/11/23 13:32:13| INFO kfcv finished [took 122.2270s]
|
||||
06/11/23 13:32:13| INFO mulne_pacc finished [took 145.0130s]
|
||||
06/11/23 13:32:22| INFO ref finished [took 122.3525s]
|
||||
06/11/23 13:32:23| INFO atc_mc finished [took 120.2587s]
|
||||
06/11/23 13:32:23| INFO atc_ne finished [took 113.5667s]
|
||||
06/11/23 13:32:23| INFO mulmc_pacc finished [took 167.7106s]
|
||||
06/11/23 13:32:36| INFO mul_cc finished [took 143.6517s]
|
||||
06/11/23 13:33:04| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00802) [took 182.2049s]
|
||||
06/11/23 13:34:23| INFO mul_pacc_gs finished [took 261.0038s]
|
||||
06/11/23 13:36:19| INFO binmc_pacc finished [took 405.9199s]
|
||||
06/11/23 13:36:31| INFO bin_sld finished [took 426.3780s]
|
||||
06/11/23 13:36:32| INFO bin_pacc finished [took 420.2833s]
|
||||
06/11/23 13:36:34| INFO binne_pacc finished [took 417.2048s]
|
||||
06/11/23 13:36:42| INFO bin_cc finished [took 394.3524s]
|
||||
06/11/23 13:37:45| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 13:38:18| INFO bin_sld_gsq finished [took 528.6956s]
|
||||
06/11/23 13:38:52| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00707) [took 544.2769s]
|
||||
06/11/23 13:39:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 628.0656s]
|
||||
06/11/23 13:40:41| INFO mul_sld_gs finished [took 673.3968s]
|
||||
06/11/23 13:41:58| INFO bin_pacc_gs finished [took 730.5371s]
|
||||
06/11/23 13:45:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 960.1061s]
|
||||
06/11/23 13:48:28| INFO bin_sld_gs finished [took 1140.6073s]
|
||||
06/11/23 13:48:28| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 1146.6395s]
|
||||
06/11/23 13:48:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 13:50:49| INFO mul_pacc finished [took 130.9408s]
|
||||
06/11/23 13:51:02| INFO doc_feat finished [took 86.2411s]
|
||||
06/11/23 13:51:07| INFO mul_sld finished [took 155.4513s]
|
||||
06/11/23 13:51:15| INFO atc_ne finished [took 101.0761s]
|
||||
06/11/23 13:51:20| INFO ref finished [took 121.3689s]
|
||||
06/11/23 13:51:20| INFO atc_mc finished [took 106.6415s]
|
||||
06/11/23 13:51:22| INFO mulmc_pacc finished [took 160.4221s]
|
||||
06/11/23 13:51:22| INFO mulne_pacc finished [took 150.1203s]
|
||||
06/11/23 13:51:25| INFO kfcv finished [took 127.5280s]
|
||||
06/11/23 13:51:35| INFO mul_cc finished [took 145.4437s]
|
||||
06/11/23 13:52:03| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00886) [took 182.0543s]
|
||||
06/11/23 13:53:23| INFO mul_pacc_gs finished [took 262.2496s]
|
||||
06/11/23 13:55:28| INFO bin_sld finished [took 417.7315s]
|
||||
06/11/23 13:55:30| INFO binmc_pacc finished [took 410.0114s]
|
||||
06/11/23 13:55:30| INFO bin_pacc finished [took 413.5912s]
|
||||
06/11/23 13:55:35| INFO binne_pacc finished [took 411.8241s]
|
||||
06/11/23 13:55:42| INFO bin_cc finished [took 396.5011s]
|
||||
06/11/23 13:56:50| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 13:57:22| INFO bin_sld_gsq finished [took 527.2507s]
|
||||
06/11/23 13:58:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00910) [took 547.7641s]
|
||||
06/11/23 13:59:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 634.8469s]
|
||||
06/11/23 13:59:54| INFO mul_sld_gs finished [took 680.2027s]
|
||||
06/11/23 14:01:07| INFO bin_pacc_gs finished [took 731.8655s]
|
||||
06/11/23 14:04:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 960.6861s]
|
||||
06/11/23 14:07:34| INFO bin_sld_gs finished [took 1141.7199s]
|
||||
06/11/23 14:07:34| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 1146.2680s]
|
||||
06/11/23 14:07:34| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 14:10:08| INFO mulmc_pacc finished [took 141.2266s]
|
||||
06/11/23 14:10:19| INFO atc_ne finished [took 101.4512s]
|
||||
06/11/23 14:10:20| INFO mul_sld finished [took 162.5808s]
|
||||
06/11/23 14:10:23| INFO mul_pacc finished [took 158.9068s]
|
||||
06/11/23 14:10:30| INFO kfcv finished [took 123.4790s]
|
||||
06/11/23 14:10:33| INFO mulne_pacc finished [took 158.4983s]
|
||||
06/11/23 14:10:33| INFO doc_feat finished [took 111.7987s]
|
||||
06/11/23 14:10:35| INFO ref finished [took 124.4184s]
|
||||
06/11/23 14:10:40| INFO atc_mc finished [took 126.3543s]
|
||||
06/11/23 14:10:40| INFO mul_cc finished [took 139.5958s]
|
||||
06/11/23 14:11:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.01309) [took 184.0645s]
|
||||
06/11/23 14:12:44| INFO mul_pacc_gs finished [took 272.5404s]
|
||||
06/11/23 14:14:32| INFO binmc_pacc finished [took 406.3609s]
|
||||
06/11/23 14:14:38| INFO bin_pacc finished [took 414.8972s]
|
||||
06/11/23 14:14:43| INFO binne_pacc finished [took 414.4123s]
|
||||
06/11/23 14:14:51| INFO bin_cc finished [took 395.5254s]
|
||||
06/11/23 14:14:55| INFO bin_sld finished [took 437.7681s]
|
||||
06/11/23 14:15:58| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 14:16:33| INFO bin_sld_gsq finished [took 532.4040s]
|
||||
06/11/23 14:16:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00812) [took 536.4746s]
|
||||
06/11/23 14:18:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 636.4067s]
|
||||
06/11/23 14:19:00| INFO mul_sld_gs finished [took 680.2467s]
|
||||
06/11/23 14:20:01| INFO bin_pacc_gs finished [took 720.9205s]
|
||||
06/11/23 14:23:33| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 954.4487s]
|
||||
06/11/23 14:26:41| INFO bin_sld_gs finished [took 1142.3328s]
|
||||
06/11/23 14:26:41| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 1146.7713s]
|
||||
06/11/23 14:26:41| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
|
||||
06/11/23 14:29:04| INFO mul_pacc finished [took 133.1736s]
|
||||
06/11/23 14:29:07| INFO ref finished [took 87.1594s]
|
||||
06/11/23 14:29:16| INFO doc_feat finished [took 83.8190s]
|
||||
06/11/23 14:29:21| INFO mulmc_pacc finished [took 147.5202s]
|
||||
06/11/23 14:29:22| INFO atc_mc finished [took 99.1039s]
|
||||
06/11/23 14:29:23| INFO kfcv finished [took 109.5348s]
|
||||
06/11/23 14:29:27| INFO mulne_pacc finished [took 148.1672s]
|
||||
06/11/23 14:29:33| INFO atc_ne finished [took 101.4673s]
|
||||
06/11/23 14:29:36| INFO mul_cc finished [took 126.0447s]
|
||||
06/11/23 14:29:42| INFO mul_sld finished [took 177.5880s]
|
||||
06/11/23 14:30:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01497) [took 175.1432s]
|
||||
06/11/23 14:31:33| INFO mul_pacc_gs finished [took 252.3399s]
|
||||
06/11/23 14:33:34| INFO binmc_pacc finished [took 401.7891s]
|
||||
06/11/23 14:33:35| INFO binne_pacc finished [took 400.4138s]
|
||||
06/11/23 14:33:36| INFO bin_pacc finished [took 406.7598s]
|
||||
06/11/23 14:33:48| INFO bin_cc finished [took 378.7595s]
|
||||
06/11/23 14:33:48| INFO bin_sld finished [took 423.7366s]
|
||||
06/11/23 14:34:47| WARNING Method mul_sld_gsq failed. Exception: 'GridSearchQ' object has no attribute 'classes_'
|
||||
06/11/23 14:35:26| INFO bin_sld_gsq finished [took 518.8996s]
|
||||
06/11/23 14:36:13| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00880) [took 539.3992s]
|
||||
06/11/23 14:37:09| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 622.0419s]
|
||||
06/11/23 14:37:53| INFO mul_sld_gs finished [took 666.0058s]
|
||||
06/11/23 14:39:16| INFO bin_pacc_gs finished [took 722.5231s]
|
||||
06/11/23 14:42:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 929.3464s]
|
||||
06/11/23 14:45:14| INFO bin_sld_gs finished [took 1108.7356s]
|
||||
06/11/23 14:45:14| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 1113.2364s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
07/11/23 01:05:25| INFO dataset rcv1_CCAT_9prevs
|
||||
07/11/23 01:05:30| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:06:23| INFO ref finished [took 48.3560s]
|
||||
07/11/23 01:06:29| INFO atc_mc finished [took 52.9929s]
|
||||
07/11/23 01:06:30| INFO atc_ne finished [took 53.3908s]
|
||||
07/11/23 01:07:06| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
07/11/23 01:11:38| INFO mul_sld_gsq finished [took 364.0698s]
|
||||
07/11/23 01:13:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00644) [took 499.4945s]
|
||||
07/11/23 01:14:34| INFO mul_sld_gs finished [took 542.6047s]
|
||||
07/11/23 01:18:02| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 750.8663s]
|
||||
07/11/23 01:21:01| INFO bin_sld_gs finished [took 930.1356s]
|
||||
07/11/23 01:21:01| INFO Dataset sample 0.10 of dataset rcv1_CCAT_9prevs finished [took 931.4321s]
|
||||
07/11/23 01:21:01| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:22:02| INFO ref finished [took 55.2212s]
|
||||
07/11/23 01:22:07| INFO atc_mc finished [took 59.3890s]
|
||||
07/11/23 01:22:09| INFO atc_ne finished [took 59.7388s]
|
||||
07/11/23 01:27:21| INFO mul_sld_gsq finished [took 375.2352s]
|
||||
07/11/23 01:27:24| INFO bin_sld_gsq finished [took 379.6159s]
|
||||
07/11/23 01:29:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01221) [took 502.0302s]
|
||||
07/11/23 01:30:08| INFO mul_sld_gs finished [took 545.0285s]
|
||||
07/11/23 01:34:25| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00768) [took 802.3620s]
|
||||
07/11/23 01:37:25| INFO bin_sld_gs finished [took 982.3260s]
|
||||
07/11/23 01:37:25| INFO Dataset sample 0.20 of dataset rcv1_CCAT_9prevs finished [took 983.7236s]
|
||||
07/11/23 01:37:25| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:38:20| INFO ref finished [took 49.9803s]
|
||||
07/11/23 01:38:25| INFO atc_mc finished [took 53.3765s]
|
||||
07/11/23 01:38:26| INFO atc_ne finished [took 53.8925s]
|
||||
07/11/23 01:43:41| INFO mul_sld_gsq finished [took 372.2608s]
|
||||
07/11/23 01:43:45| INFO bin_sld_gsq finished [took 377.3380s]
|
||||
07/11/23 01:45:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00872) [took 497.5768s]
|
||||
07/11/23 01:46:28| INFO mul_sld_gs finished [took 540.8267s]
|
||||
07/11/23 01:51:09| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00782) [took 822.2849s]
|
||||
07/11/23 01:54:10| INFO bin_sld_gs finished [took 1003.7804s]
|
||||
07/11/23 01:54:10| INFO Dataset sample 0.30 of dataset rcv1_CCAT_9prevs finished [took 1005.2506s]
|
||||
07/11/23 01:54:10| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 01:55:05| INFO ref finished [took 49.8884s]
|
||||
07/11/23 01:55:09| INFO atc_mc finished [took 53.3594s]
|
||||
07/11/23 01:55:10| INFO atc_ne finished [took 53.5162s]
|
||||
07/11/23 02:00:25| INFO mul_sld_gsq finished [took 371.4460s]
|
||||
07/11/23 02:00:41| INFO bin_sld_gsq finished [took 387.6183s]
|
||||
07/11/23 02:02:30| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01037) [took 498.0096s]
|
||||
07/11/23 02:03:11| INFO mul_sld_gs finished [took 539.1531s]
|
||||
07/11/23 02:07:53| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01112) [took 821.8730s]
|
||||
07/11/23 02:10:52| INFO bin_sld_gs finished [took 1001.0803s]
|
||||
07/11/23 02:10:52| INFO Dataset sample 0.40 of dataset rcv1_CCAT_9prevs finished [took 1002.3085s]
|
||||
07/11/23 02:10:52| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 02:11:44| INFO ref finished [took 47.2218s]
|
||||
07/11/23 02:11:48| INFO atc_mc finished [took 49.6349s]
|
||||
07/11/23 02:11:50| INFO atc_ne finished [took 50.9082s]
|
||||
07/11/23 02:16:51| INFO mul_sld_gsq finished [took 354.3706s]
|
||||
07/11/23 02:17:11| INFO bin_sld_gsq finished [took 376.0124s]
|
||||
07/11/23 02:18:51| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00572) [took 476.0587s]
|
||||
07/11/23 02:19:33| INFO mul_sld_gs finished [took 518.5692s]
|
||||
07/11/23 02:24:17| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00653) [took 803.4978s]
|
||||
07/11/23 02:27:16| INFO bin_sld_gs finished [took 982.4395s]
|
||||
07/11/23 02:27:16| INFO Dataset sample 0.50 of dataset rcv1_CCAT_9prevs finished [took 983.7838s]
|
||||
07/11/23 02:27:16| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 02:28:08| INFO ref finished [took 46.6191s]
|
||||
07/11/23 02:28:13| INFO atc_mc finished [took 50.3543s]
|
||||
07/11/23 02:28:15| INFO atc_ne finished [took 51.6601s]
|
||||
07/11/23 02:33:15| INFO mul_sld_gsq finished [took 354.6014s]
|
||||
07/11/23 02:33:34| INFO bin_sld_gsq finished [took 374.7872s]
|
||||
07/11/23 02:35:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00637) [took 475.9302s]
|
||||
07/11/23 02:35:57| INFO mul_sld_gs finished [took 518.5425s]
|
||||
07/11/23 02:40:20| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00544) [took 782.7268s]
|
||||
07/11/23 02:43:18| INFO bin_sld_gs finished [took 960.6334s]
|
||||
07/11/23 02:43:18| INFO Dataset sample 0.60 of dataset rcv1_CCAT_9prevs finished [took 961.9030s]
|
||||
07/11/23 02:43:18| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 02:44:10| INFO ref finished [took 47.1234s]
|
||||
07/11/23 02:44:14| INFO atc_mc finished [took 49.9871s]
|
||||
07/11/23 02:44:16| INFO atc_ne finished [took 50.9160s]
|
||||
07/11/23 02:49:19| INFO mul_sld_gsq finished [took 357.0613s]
|
||||
07/11/23 02:49:30| INFO bin_sld_gsq finished [took 368.8000s]
|
||||
07/11/23 02:51:16| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00765) [took 475.7332s]
|
||||
07/11/23 02:51:59| INFO mul_sld_gs finished [took 518.6671s]
|
||||
07/11/23 02:56:28| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01235) [took 788.7117s]
|
||||
07/11/23 02:59:28| INFO bin_sld_gs finished [took 968.7653s]
|
||||
07/11/23 02:59:28| INFO Dataset sample 0.70 of dataset rcv1_CCAT_9prevs finished [took 970.1516s]
|
||||
07/11/23 02:59:28| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 03:00:20| INFO ref finished [took 46.9898s]
|
||||
07/11/23 03:00:24| INFO atc_mc finished [took 49.8768s]
|
||||
07/11/23 03:00:25| INFO atc_ne finished [took 49.6324s]
|
||||
07/11/23 03:05:23| INFO mul_sld_gsq finished [took 350.7932s]
|
||||
07/11/23 03:05:32| INFO bin_sld_gsq finished [took 360.8665s]
|
||||
07/11/23 03:07:25| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.01306) [took 474.6581s]
|
||||
07/11/23 03:08:07| INFO mul_sld_gs finished [took 516.4890s]
|
||||
07/11/23 03:12:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00894) [took 774.9140s]
|
||||
07/11/23 03:15:29| INFO bin_sld_gs finished [took 959.3579s]
|
||||
07/11/23 03:15:29| INFO Dataset sample 0.80 of dataset rcv1_CCAT_9prevs finished [took 960.6992s]
|
||||
07/11/23 03:15:29| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs started
|
||||
07/11/23 03:16:21| INFO ref finished [took 47.3281s]
|
||||
07/11/23 03:16:25| INFO atc_mc finished [took 49.8016s]
|
||||
07/11/23 03:16:28| INFO atc_ne finished [took 51.2288s]
|
||||
07/11/23 03:21:16| INFO mul_sld_gsq finished [took 343.2861s]
|
||||
07/11/23 03:21:22| INFO bin_sld_gsq finished [took 349.6065s]
|
||||
07/11/23 03:23:20| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00808) [took 468.7910s]
|
||||
07/11/23 03:24:01| INFO mul_sld_gs finished [took 509.9001s]
|
||||
07/11/23 03:28:03| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00604) [took 752.8185s]
|
||||
07/11/23 03:31:01| INFO bin_sld_gs finished [took 930.3934s]
|
||||
07/11/23 03:31:01| INFO Dataset sample 0.90 of dataset rcv1_CCAT_9prevs finished [took 931.7055s]
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
|
|
@ -1,341 +1,341 @@
|
|||
06/11/23 06:18:54| INFO dataset rcv1_GCAT_9prevs
|
||||
06/11/23 06:18:59| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:19:11| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:19:11| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:19:54| INFO ref finished [took 42.0769s]
|
||||
06/11/23 06:19:59| INFO atc_mc finished [took 45.5011s]
|
||||
06/11/23 06:20:14| INFO mulne_sld finished [took 66.0516s]
|
||||
06/11/23 06:20:15| INFO mul_sld finished [took 73.1171s]
|
||||
06/11/23 06:20:17| INFO mulmc_sld finished [took 72.1930s]
|
||||
06/11/23 06:22:23| INFO bin_sld finished [took 203.0368s]
|
||||
06/11/23 06:22:27| INFO binmc_sld finished [took 203.2975s]
|
||||
06/11/23 06:22:29| INFO binne_sld finished [took 202.7501s]
|
||||
06/11/23 06:22:29| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 210.2201s]
|
||||
06/11/23 06:22:29| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:23:26| INFO ref finished [took 46.6022s]
|
||||
06/11/23 06:23:31| INFO atc_mc finished [took 50.3293s]
|
||||
06/11/23 06:23:33| INFO mul_pacc finished [took 54.9265s]
|
||||
06/11/23 06:23:46| INFO mul_sld finished [took 74.9035s]
|
||||
06/11/23 06:23:52| INFO mulne_sld finished [took 76.2697s]
|
||||
06/11/23 06:23:54| INFO mulmc_sld finished [took 80.8754s]
|
||||
06/11/23 06:26:06| INFO bin_pacc finished [took 209.7751s]
|
||||
06/11/23 06:26:08| INFO bin_sld finished [took 217.8889s]
|
||||
06/11/23 06:26:13| INFO binmc_sld finished [took 220.7753s]
|
||||
06/11/23 06:26:14| INFO binne_sld finished [took 219.7510s]
|
||||
06/11/23 06:26:14| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 224.9268s]
|
||||
06/11/23 06:26:14| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:27:10| INFO ref finished [took 46.4938s]
|
||||
06/11/23 06:27:16| INFO atc_mc finished [took 50.5904s]
|
||||
06/11/23 06:27:18| INFO mul_pacc finished [took 55.4949s]
|
||||
06/11/23 06:27:26| INFO mulmc_sld finished [took 67.7140s]
|
||||
06/11/23 06:27:26| INFO mul_sld finished [took 70.0891s]
|
||||
06/11/23 06:27:28| INFO mulne_sld finished [took 68.1806s]
|
||||
06/11/23 06:29:50| INFO bin_pacc finished [took 208.6091s]
|
||||
06/11/23 06:29:51| INFO binmc_sld finished [took 213.7985s]
|
||||
06/11/23 06:29:51| INFO bin_sld finished [took 215.8158s]
|
||||
06/11/23 06:29:55| INFO binne_sld finished [took 215.5523s]
|
||||
06/11/23 06:29:55| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 220.4589s]
|
||||
06/11/23 06:29:55| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:30:51| INFO ref finished [took 46.3752s]
|
||||
06/11/23 06:30:56| INFO atc_mc finished [took 50.7062s]
|
||||
06/11/23 06:30:58| INFO mul_pacc finished [took 55.2260s]
|
||||
06/11/23 06:31:01| INFO mul_sld finished [took 64.2359s]
|
||||
06/11/23 06:31:02| INFO mulmc_sld finished [took 63.5099s]
|
||||
06/11/23 06:31:04| INFO mulne_sld finished [took 62.9188s]
|
||||
06/11/23 06:33:29| INFO bin_sld finished [took 213.2716s]
|
||||
06/11/23 06:33:30| INFO bin_pacc finished [took 208.6574s]
|
||||
06/11/23 06:33:31| INFO binmc_sld finished [took 213.1856s]
|
||||
06/11/23 06:33:33| INFO binne_sld finished [took 213.2771s]
|
||||
06/11/23 06:33:33| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 218.1742s]
|
||||
06/11/23 06:33:33| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:34:29| INFO ref finished [took 46.6793s]
|
||||
06/11/23 06:34:34| INFO atc_mc finished [took 50.9915s]
|
||||
06/11/23 06:34:37| INFO mul_pacc finished [took 55.9725s]
|
||||
06/11/23 06:34:38| INFO mul_sld finished [took 63.1317s]
|
||||
06/11/23 06:34:40| INFO mulmc_sld finished [took 62.7473s]
|
||||
06/11/23 06:34:41| INFO mulne_sld finished [took 62.1303s]
|
||||
06/11/23 06:37:08| INFO bin_pacc finished [took 207.7854s]
|
||||
06/11/23 06:37:08| INFO bin_sld finished [took 213.7945s]
|
||||
06/11/23 06:37:08| INFO binmc_sld finished [took 212.6207s]
|
||||
06/11/23 06:37:12| INFO binne_sld finished [took 213.8742s]
|
||||
06/11/23 06:37:12| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 218.7265s]
|
||||
06/11/23 06:37:12| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:38:08| INFO ref finished [took 46.6057s]
|
||||
06/11/23 06:38:14| INFO atc_mc finished [took 51.1055s]
|
||||
06/11/23 06:38:15| INFO mul_pacc finished [took 55.5338s]
|
||||
06/11/23 06:38:17| INFO mul_sld finished [took 63.2113s]
|
||||
06/11/23 06:38:18| INFO mulmc_sld finished [took 62.2265s]
|
||||
06/11/23 06:38:20| INFO mulne_sld finished [took 61.9918s]
|
||||
06/11/23 06:40:46| INFO bin_pacc finished [took 207.5094s]
|
||||
06/11/23 06:40:46| INFO bin_sld finished [took 213.6350s]
|
||||
06/11/23 06:40:47| INFO binmc_sld finished [took 212.8363s]
|
||||
06/11/23 06:40:49| INFO binne_sld finished [took 212.2587s]
|
||||
06/11/23 06:40:49| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 217.1976s]
|
||||
06/11/23 06:40:49| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:41:44| INFO ref finished [took 45.9582s]
|
||||
06/11/23 06:41:50| INFO atc_mc finished [took 50.0401s]
|
||||
06/11/23 06:41:54| INFO mul_sld finished [took 62.6045s]
|
||||
06/11/23 06:41:54| INFO mulmc_sld finished [took 61.4168s]
|
||||
06/11/23 06:41:56| INFO mulne_sld finished [took 61.3708s]
|
||||
06/11/23 06:42:00| INFO mul_pacc finished [took 62.6486s]
|
||||
06/11/23 06:44:23| INFO bin_sld finished [took 212.5992s]
|
||||
06/11/23 06:44:23| INFO bin_pacc finished [took 207.5241s]
|
||||
06/11/23 06:44:24| INFO binmc_sld finished [took 212.2794s]
|
||||
06/11/23 06:44:27| INFO binne_sld finished [took 212.8325s]
|
||||
06/11/23 06:44:27| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 217.7909s]
|
||||
06/11/23 06:44:27| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:45:23| INFO ref finished [took 46.6997s]
|
||||
06/11/23 06:45:28| INFO atc_mc finished [took 50.6417s]
|
||||
06/11/23 06:45:30| INFO mul_sld finished [took 61.5352s]
|
||||
06/11/23 06:45:31| INFO mul_pacc finished [took 55.9055s]
|
||||
06/11/23 06:45:31| INFO mulmc_sld finished [took 60.6608s]
|
||||
06/11/23 06:45:33| INFO mulne_sld finished [took 60.1616s]
|
||||
06/11/23 06:48:01| INFO bin_pacc finished [took 207.7543s]
|
||||
06/11/23 06:48:02| INFO bin_sld finished [took 213.7056s]
|
||||
06/11/23 06:48:03| INFO binmc_sld finished [took 213.7901s]
|
||||
06/11/23 06:48:04| INFO binne_sld finished [took 212.4421s]
|
||||
06/11/23 06:48:04| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 217.4465s]
|
||||
06/11/23 06:48:04| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:48:06| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:07| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:09| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:11| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:13| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 06:48:49| INFO ref finished [took 36.4085s]
|
||||
06/11/23 06:48:53| INFO atc_mc finished [took 39.1380s]
|
||||
06/11/23 06:48:54| INFO mulmc_sld finished [took 46.0254s]
|
||||
06/11/23 06:48:55| INFO mulne_sld finished [took 45.1935s]
|
||||
06/11/23 06:49:00| INFO mul_sld finished [took 53.9145s]
|
||||
06/11/23 06:49:00| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 55.9159s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 18:04:06| INFO dataset rcv1_GCAT_9prevs
|
||||
06/11/23 18:04:12| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:04:19| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:21| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:22| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:24| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:24| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:26| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:27| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:28| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:29| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:05:10| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 18:05:41| INFO ref finished [took 65.3048s]
|
||||
06/11/23 18:05:43| INFO kfcv finished [took 66.9585s]
|
||||
06/11/23 18:05:45| INFO doc_feat finished [took 56.7504s]
|
||||
06/11/23 18:05:49| INFO mul_cc finished [took 77.6035s]
|
||||
06/11/23 18:05:49| INFO atc_mc finished [took 66.4650s]
|
||||
06/11/23 18:05:52| INFO atc_ne finished [took 65.1035s]
|
||||
06/11/23 18:05:52| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:05:56| INFO mul_sld finished [took 101.3427s]
|
||||
06/11/23 18:08:12| INFO bin_sld finished [took 238.6323s]
|
||||
06/11/23 18:08:21| INFO bin_cc finished [took 230.3034s]
|
||||
06/11/23 18:10:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00897) [took 402.3046s]
|
||||
06/11/23 18:11:39| INFO mul_sld_gs finished [took 441.7473s]
|
||||
06/11/23 18:11:39| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 446.6543s]
|
||||
06/11/23 18:11:39| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:14:11| INFO mulmc_pacc finished [took 140.5240s]
|
||||
06/11/23 18:14:13| INFO kfcv finished [took 108.3325s]
|
||||
06/11/23 18:14:16| INFO doc_feat finished [took 91.1407s]
|
||||
06/11/23 18:14:21| INFO atc_ne finished [took 96.9645s]
|
||||
06/11/23 18:14:22| INFO mul_pacc finished [took 154.9757s]
|
||||
06/11/23 18:14:36| INFO ref finished [took 118.1583s]
|
||||
06/11/23 18:14:37| INFO atc_mc finished [took 118.5016s]
|
||||
06/11/23 18:14:41| INFO mulne_pacc finished [took 157.8831s]
|
||||
06/11/23 18:14:49| INFO mul_cc finished [took 144.8053s]
|
||||
06/11/23 18:14:50| INFO mul_sld finished [took 188.8450s]
|
||||
06/11/23 18:15:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01452) [took 184.0929s]
|
||||
06/11/23 18:16:33| INFO mul_pacc_gs finished [took 258.2234s]
|
||||
06/11/23 18:18:46| INFO binmc_pacc finished [took 417.1372s]
|
||||
06/11/23 18:18:48| INFO bin_pacc finished [took 422.0619s]
|
||||
06/11/23 18:18:52| INFO bin_sld finished [took 431.4426s]
|
||||
06/11/23 18:18:56| INFO binne_pacc finished [took 421.5812s]
|
||||
06/11/23 18:19:02| INFO bin_cc finished [took 402.4673s]
|
||||
06/11/23 18:19:32| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 18:20:26| INFO bin_sld_gsq finished [took 522.0734s]
|
||||
06/11/23 18:21:11| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 540.4022s]
|
||||
06/11/23 18:21:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00821) [took 600.6611s]
|
||||
06/11/23 18:22:25| INFO mul_sld_gs finished [took 642.1063s]
|
||||
06/11/23 18:24:14| INFO bin_pacc_gs finished [took 723.2605s]
|
||||
06/11/23 18:26:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00816) [took 911.5066s]
|
||||
06/11/23 18:29:56| INFO bin_sld_gs finished [took 1093.4674s]
|
||||
06/11/23 18:29:56| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 1096.7184s]
|
||||
06/11/23 18:29:56| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:32:21| INFO ref finished [took 89.3355s]
|
||||
06/11/23 18:32:33| INFO doc_feat finished [took 91.9119s]
|
||||
06/11/23 18:32:35| INFO mulmc_pacc finished [took 147.2084s]
|
||||
06/11/23 18:32:38| INFO mulne_pacc finished [took 137.0643s]
|
||||
06/11/23 18:32:54| INFO atc_mc finished [took 117.6847s]
|
||||
06/11/23 18:32:56| INFO kfcv finished [took 129.8598s]
|
||||
06/11/23 18:33:00| INFO mul_pacc finished [took 174.5769s]
|
||||
06/11/23 18:33:00| INFO mul_sld finished [took 181.1734s]
|
||||
06/11/23 18:33:03| INFO atc_ne finished [took 123.9984s]
|
||||
06/11/23 18:33:09| INFO mul_cc finished [took 148.8635s]
|
||||
06/11/23 18:33:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00629) [took 177.7598s]
|
||||
06/11/23 18:34:51| INFO mul_pacc_gs finished [took 256.4186s]
|
||||
06/11/23 18:37:10| INFO bin_pacc finished [took 425.7912s]
|
||||
06/11/23 18:37:12| INFO binmc_pacc finished [took 425.7599s]
|
||||
06/11/23 18:37:14| INFO binne_pacc finished [took 424.0101s]
|
||||
06/11/23 18:37:18| INFO bin_sld finished [took 440.4389s]
|
||||
06/11/23 18:37:22| INFO bin_cc finished [took 407.2413s]
|
||||
06/11/23 18:37:52| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 18:38:51| INFO bin_sld_gsq finished [took 529.6242s]
|
||||
06/11/23 18:39:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00489) [took 541.8062s]
|
||||
06/11/23 18:40:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00615) [took 601.7630s]
|
||||
06/11/23 18:40:45| INFO mul_sld_gs finished [took 644.5111s]
|
||||
06/11/23 18:42:37| INFO bin_pacc_gs finished [took 729.3942s]
|
||||
06/11/23 18:45:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00490) [took 936.3088s]
|
||||
06/11/23 18:48:37| INFO bin_sld_gs finished [took 1117.0610s]
|
||||
06/11/23 18:48:37| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 1120.9681s]
|
||||
06/11/23 18:48:37| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:51:02| INFO doc_feat finished [took 79.6380s]
|
||||
06/11/23 18:51:20| INFO mulne_pacc finished [took 144.5625s]
|
||||
06/11/23 18:51:30| INFO mul_sld finished [took 171.1473s]
|
||||
06/11/23 18:51:35| INFO mulmc_pacc finished [took 166.1468s]
|
||||
06/11/23 18:51:39| INFO mul_pacc finished [took 172.9449s]
|
||||
06/11/23 18:51:43| INFO ref finished [took 132.2492s]
|
||||
06/11/23 18:51:45| INFO kfcv finished [took 137.9538s]
|
||||
06/11/23 18:51:52| INFO atc_mc finished [took 137.7185s]
|
||||
06/11/23 18:51:54| INFO atc_ne finished [took 134.1066s]
|
||||
06/11/23 18:51:59| INFO mul_cc finished [took 159.0670s]
|
||||
06/11/23 18:52:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01049) [took 180.3366s]
|
||||
06/11/23 18:53:38| INFO mul_pacc_gs finished [took 266.6075s]
|
||||
06/11/23 18:56:00| INFO bin_sld finished [took 441.9022s]
|
||||
06/11/23 18:56:02| INFO binne_pacc finished [took 431.1354s]
|
||||
06/11/23 18:56:02| INFO binmc_pacc finished [took 434.5268s]
|
||||
06/11/23 18:56:04| INFO bin_pacc finished [took 438.8400s]
|
||||
06/11/23 18:56:07| INFO bin_cc finished [took 412.8827s]
|
||||
06/11/23 18:56:38| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 18:57:38| INFO bin_sld_gsq finished [took 534.9970s]
|
||||
06/11/23 18:58:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.5790s]
|
||||
06/11/23 18:58:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00692) [took 616.7506s]
|
||||
06/11/23 18:59:43| INFO mul_sld_gs finished [took 661.6976s]
|
||||
06/11/23 19:01:20| INFO bin_pacc_gs finished [took 735.1934s]
|
||||
06/11/23 19:04:29| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00601) [took 948.3129s]
|
||||
06/11/23 19:07:30| INFO bin_sld_gs finished [took 1129.1432s]
|
||||
06/11/23 19:07:30| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 1133.2853s]
|
||||
06/11/23 19:07:30| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 19:10:11| INFO doc_feat finished [took 90.8028s]
|
||||
06/11/23 19:10:12| INFO mul_sld finished [took 159.3725s]
|
||||
06/11/23 19:10:17| INFO atc_mc finished [took 108.3872s]
|
||||
06/11/23 19:10:20| INFO mulmc_pacc finished [took 158.7937s]
|
||||
06/11/23 19:10:27| INFO kfcv finished [took 125.4384s]
|
||||
06/11/23 19:10:32| INFO mul_cc finished [took 134.1449s]
|
||||
06/11/23 19:10:33| INFO atc_ne finished [took 115.0137s]
|
||||
06/11/23 19:10:33| INFO mul_pacc finished [took 173.4398s]
|
||||
06/11/23 19:10:35| INFO ref finished [took 127.6900s]
|
||||
06/11/23 19:10:35| INFO mulne_pacc finished [took 158.1989s]
|
||||
06/11/23 19:11:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00893) [took 181.2645s]
|
||||
06/11/23 19:12:28| INFO mul_pacc_gs finished [took 263.1619s]
|
||||
06/11/23 19:14:45| INFO bin_sld finished [took 432.8401s]
|
||||
06/11/23 19:14:48| INFO bin_pacc finished [took 430.1210s]
|
||||
06/11/23 19:14:54| INFO binmc_pacc finished [took 433.8715s]
|
||||
06/11/23 19:14:58| INFO bin_cc finished [took 405.7688s]
|
||||
06/11/23 19:14:59| INFO binne_pacc finished [took 435.7315s]
|
||||
06/11/23 19:15:29| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 19:16:36| INFO bin_sld_gsq finished [took 539.4078s]
|
||||
06/11/23 19:17:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00831) [took 545.8362s]
|
||||
06/11/23 19:17:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00797) [took 609.7895s]
|
||||
06/11/23 19:18:32| INFO mul_sld_gs finished [took 657.1765s]
|
||||
06/11/23 19:20:08| INFO bin_pacc_gs finished [took 728.9184s]
|
||||
06/11/23 19:23:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00738) [took 966.8750s]
|
||||
06/11/23 19:26:42| INFO bin_sld_gs finished [took 1148.2428s]
|
||||
06/11/23 19:26:42| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 1152.4463s]
|
||||
06/11/23 19:26:43| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 19:29:16| INFO mul_pacc finished [took 142.3375s]
|
||||
06/11/23 19:29:26| INFO doc_feat finished [took 92.0123s]
|
||||
06/11/23 19:29:29| INFO atc_ne finished [took 96.1697s]
|
||||
06/11/23 19:29:32| INFO mul_sld finished [took 164.7852s]
|
||||
06/11/23 19:29:33| INFO ref finished [took 114.3664s]
|
||||
06/11/23 19:29:36| INFO kfcv finished [took 118.4300s]
|
||||
06/11/23 19:29:37| INFO atc_mc finished [took 111.6950s]
|
||||
06/11/23 19:29:37| INFO mul_cc finished [took 127.8860s]
|
||||
06/11/23 19:29:39| INFO mulmc_pacc finished [took 162.5217s]
|
||||
06/11/23 19:29:46| INFO mulne_pacc finished [took 159.7535s]
|
||||
06/11/23 19:30:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.2267s]
|
||||
06/11/23 19:31:42| INFO mul_pacc_gs finished [took 263.2959s]
|
||||
06/11/23 19:33:48| INFO bin_pacc finished [took 415.7355s]
|
||||
06/11/23 19:33:49| INFO binne_pacc finished [took 411.7032s]
|
||||
06/11/23 19:33:49| INFO bin_sld finished [took 423.6935s]
|
||||
06/11/23 19:33:56| INFO binmc_pacc finished [took 422.0731s]
|
||||
06/11/23 19:34:02| INFO bin_cc finished [took 394.8074s]
|
||||
06/11/23 19:34:45| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 19:35:33| INFO bin_sld_gsq finished [took 523.6794s]
|
||||
06/11/23 19:36:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00651) [took 539.0149s]
|
||||
06/11/23 19:36:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00646) [took 605.4721s]
|
||||
06/11/23 19:37:37| INFO mul_sld_gs finished [took 647.9998s]
|
||||
06/11/23 19:39:13| INFO bin_pacc_gs finished [took 722.3065s]
|
||||
06/11/23 19:42:14| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00635) [took 926.2548s]
|
||||
06/11/23 19:45:13| INFO bin_sld_gs finished [took 1105.8303s]
|
||||
06/11/23 19:45:13| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 1110.5345s]
|
||||
06/11/23 19:45:13| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 19:47:55| INFO mul_pacc finished [took 151.2717s]
|
||||
06/11/23 19:48:01| INFO mul_sld finished [took 164.7303s]
|
||||
06/11/23 19:48:02| INFO doc_feat finished [took 95.7218s]
|
||||
06/11/23 19:48:20| INFO kfcv finished [took 132.6414s]
|
||||
06/11/23 19:48:26| INFO ref finished [took 136.4855s]
|
||||
06/11/23 19:48:27| INFO mulmc_pacc finished [took 180.2510s]
|
||||
06/11/23 19:48:30| INFO mulne_pacc finished [took 173.6996s]
|
||||
06/11/23 19:48:33| INFO atc_mc finished [took 135.5939s]
|
||||
06/11/23 19:48:34| INFO atc_ne finished [took 129.3719s]
|
||||
06/11/23 19:48:35| INFO mul_cc finished [took 153.9587s]
|
||||
06/11/23 19:48:47| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00782) [took 177.0918s]
|
||||
06/11/23 19:50:13| INFO mul_pacc_gs finished [took 262.7047s]
|
||||
06/11/23 19:52:34| INFO bin_pacc finished [took 431.9695s]
|
||||
06/11/23 19:52:36| INFO binmc_pacc finished [took 430.1566s]
|
||||
06/11/23 19:52:43| INFO bin_sld finished [took 446.4452s]
|
||||
06/11/23 19:52:44| INFO bin_cc finished [took 407.8850s]
|
||||
06/11/23 19:52:47| INFO binne_pacc finished [took 438.4423s]
|
||||
06/11/23 19:53:19| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 19:54:09| INFO bin_sld_gsq finished [took 528.9254s]
|
||||
06/11/23 19:54:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00669) [took 545.8164s]
|
||||
06/11/23 19:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00814) [took 619.0258s]
|
||||
06/11/23 19:56:21| INFO mul_sld_gs finished [took 661.4303s]
|
||||
06/11/23 19:57:51| INFO bin_pacc_gs finished [took 733.3970s]
|
||||
06/11/23 20:00:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00795) [took 935.9973s]
|
||||
06/11/23 20:03:55| INFO bin_sld_gs finished [took 1117.3981s]
|
||||
06/11/23 20:03:55| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 1121.8060s]
|
||||
06/11/23 20:03:55| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 20:06:27| INFO mul_sld finished [took 147.0727s]
|
||||
06/11/23 20:06:30| INFO doc_feat finished [took 81.1117s]
|
||||
06/11/23 20:06:48| INFO mul_pacc finished [took 162.2312s]
|
||||
06/11/23 20:07:04| INFO kfcv finished [took 133.4389s]
|
||||
06/11/23 20:07:04| INFO ref finished [took 132.6728s]
|
||||
06/11/23 20:07:05| INFO mulne_pacc finished [took 171.0782s]
|
||||
06/11/23 20:07:08| INFO mulmc_pacc finished [took 179.6909s]
|
||||
06/11/23 20:07:10| INFO atc_mc finished [took 130.5941s]
|
||||
06/11/23 20:07:14| INFO mul_cc finished [took 150.3795s]
|
||||
06/11/23 20:07:15| INFO atc_ne finished [took 131.0309s]
|
||||
06/11/23 20:07:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00813) [took 177.7289s]
|
||||
06/11/23 20:08:49| INFO mul_pacc_gs finished [took 257.9675s]
|
||||
06/11/23 20:10:44| INFO bin_pacc finished [took 399.4800s]
|
||||
06/11/23 21:01:51| INFO bin_pacc_gs finished [took 3446.1854s]
|
||||
06/11/23 21:03:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00684) [took 3563.0699s]
|
||||
06/11/23 21:04:07| INFO mul_sld_gs finished [took 3606.0194s]
|
||||
06/11/23 21:08:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00519) [took 3863.9570s]
|
||||
06/11/23 21:11:26| INFO bin_sld_gs finished [took 4046.4500s]
|
||||
06/11/23 21:11:26| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 4051.2016s]
|
||||
06/11/23 21:11:26| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 21:11:31| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:32| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:34| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:35| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
|
||||
06/11/23 21:11:36| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:38| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:38| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:40| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:40| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:42| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:42| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:44| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:12:27| INFO mul_sld finished [took 56.8958s]
|
||||
06/11/23 21:12:32| INFO ref finished [took 44.3311s]
|
||||
06/11/23 21:12:32| INFO doc_feat finished [took 41.1551s]
|
||||
06/11/23 21:12:33| INFO kfcv finished [took 46.1873s]
|
||||
06/11/23 21:12:36| INFO atc_mc finished [took 47.9541s]
|
||||
06/11/23 21:12:37| INFO mul_cc finished [took 51.8838s]
|
||||
06/11/23 21:12:37| INFO atc_ne finished [took 47.4962s]
|
||||
06/11/23 21:16:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00843) [took 312.8612s]
|
||||
06/11/23 21:17:24| INFO mul_sld_gs finished [took 351.5693s]
|
||||
06/11/23 21:17:24| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 357.7321s]
|
||||
06/11/23 06:18:54| INFO dataset rcv1_GCAT_9prevs
|
||||
06/11/23 06:18:59| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:19:11| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:19:11| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 06:19:54| INFO ref finished [took 42.0769s]
|
||||
06/11/23 06:19:59| INFO atc_mc finished [took 45.5011s]
|
||||
06/11/23 06:20:14| INFO mulne_sld finished [took 66.0516s]
|
||||
06/11/23 06:20:15| INFO mul_sld finished [took 73.1171s]
|
||||
06/11/23 06:20:17| INFO mulmc_sld finished [took 72.1930s]
|
||||
06/11/23 06:22:23| INFO bin_sld finished [took 203.0368s]
|
||||
06/11/23 06:22:27| INFO binmc_sld finished [took 203.2975s]
|
||||
06/11/23 06:22:29| INFO binne_sld finished [took 202.7501s]
|
||||
06/11/23 06:22:29| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 210.2201s]
|
||||
06/11/23 06:22:29| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:23:26| INFO ref finished [took 46.6022s]
|
||||
06/11/23 06:23:31| INFO atc_mc finished [took 50.3293s]
|
||||
06/11/23 06:23:33| INFO mul_pacc finished [took 54.9265s]
|
||||
06/11/23 06:23:46| INFO mul_sld finished [took 74.9035s]
|
||||
06/11/23 06:23:52| INFO mulne_sld finished [took 76.2697s]
|
||||
06/11/23 06:23:54| INFO mulmc_sld finished [took 80.8754s]
|
||||
06/11/23 06:26:06| INFO bin_pacc finished [took 209.7751s]
|
||||
06/11/23 06:26:08| INFO bin_sld finished [took 217.8889s]
|
||||
06/11/23 06:26:13| INFO binmc_sld finished [took 220.7753s]
|
||||
06/11/23 06:26:14| INFO binne_sld finished [took 219.7510s]
|
||||
06/11/23 06:26:14| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 224.9268s]
|
||||
06/11/23 06:26:14| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:27:10| INFO ref finished [took 46.4938s]
|
||||
06/11/23 06:27:16| INFO atc_mc finished [took 50.5904s]
|
||||
06/11/23 06:27:18| INFO mul_pacc finished [took 55.4949s]
|
||||
06/11/23 06:27:26| INFO mulmc_sld finished [took 67.7140s]
|
||||
06/11/23 06:27:26| INFO mul_sld finished [took 70.0891s]
|
||||
06/11/23 06:27:28| INFO mulne_sld finished [took 68.1806s]
|
||||
06/11/23 06:29:50| INFO bin_pacc finished [took 208.6091s]
|
||||
06/11/23 06:29:51| INFO binmc_sld finished [took 213.7985s]
|
||||
06/11/23 06:29:51| INFO bin_sld finished [took 215.8158s]
|
||||
06/11/23 06:29:55| INFO binne_sld finished [took 215.5523s]
|
||||
06/11/23 06:29:55| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 220.4589s]
|
||||
06/11/23 06:29:55| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:30:51| INFO ref finished [took 46.3752s]
|
||||
06/11/23 06:30:56| INFO atc_mc finished [took 50.7062s]
|
||||
06/11/23 06:30:58| INFO mul_pacc finished [took 55.2260s]
|
||||
06/11/23 06:31:01| INFO mul_sld finished [took 64.2359s]
|
||||
06/11/23 06:31:02| INFO mulmc_sld finished [took 63.5099s]
|
||||
06/11/23 06:31:04| INFO mulne_sld finished [took 62.9188s]
|
||||
06/11/23 06:33:29| INFO bin_sld finished [took 213.2716s]
|
||||
06/11/23 06:33:30| INFO bin_pacc finished [took 208.6574s]
|
||||
06/11/23 06:33:31| INFO binmc_sld finished [took 213.1856s]
|
||||
06/11/23 06:33:33| INFO binne_sld finished [took 213.2771s]
|
||||
06/11/23 06:33:33| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 218.1742s]
|
||||
06/11/23 06:33:33| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:34:29| INFO ref finished [took 46.6793s]
|
||||
06/11/23 06:34:34| INFO atc_mc finished [took 50.9915s]
|
||||
06/11/23 06:34:37| INFO mul_pacc finished [took 55.9725s]
|
||||
06/11/23 06:34:38| INFO mul_sld finished [took 63.1317s]
|
||||
06/11/23 06:34:40| INFO mulmc_sld finished [took 62.7473s]
|
||||
06/11/23 06:34:41| INFO mulne_sld finished [took 62.1303s]
|
||||
06/11/23 06:37:08| INFO bin_pacc finished [took 207.7854s]
|
||||
06/11/23 06:37:08| INFO bin_sld finished [took 213.7945s]
|
||||
06/11/23 06:37:08| INFO binmc_sld finished [took 212.6207s]
|
||||
06/11/23 06:37:12| INFO binne_sld finished [took 213.8742s]
|
||||
06/11/23 06:37:12| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 218.7265s]
|
||||
06/11/23 06:37:12| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:38:08| INFO ref finished [took 46.6057s]
|
||||
06/11/23 06:38:14| INFO atc_mc finished [took 51.1055s]
|
||||
06/11/23 06:38:15| INFO mul_pacc finished [took 55.5338s]
|
||||
06/11/23 06:38:17| INFO mul_sld finished [took 63.2113s]
|
||||
06/11/23 06:38:18| INFO mulmc_sld finished [took 62.2265s]
|
||||
06/11/23 06:38:20| INFO mulne_sld finished [took 61.9918s]
|
||||
06/11/23 06:40:46| INFO bin_pacc finished [took 207.5094s]
|
||||
06/11/23 06:40:46| INFO bin_sld finished [took 213.6350s]
|
||||
06/11/23 06:40:47| INFO binmc_sld finished [took 212.8363s]
|
||||
06/11/23 06:40:49| INFO binne_sld finished [took 212.2587s]
|
||||
06/11/23 06:40:49| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 217.1976s]
|
||||
06/11/23 06:40:49| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:41:44| INFO ref finished [took 45.9582s]
|
||||
06/11/23 06:41:50| INFO atc_mc finished [took 50.0401s]
|
||||
06/11/23 06:41:54| INFO mul_sld finished [took 62.6045s]
|
||||
06/11/23 06:41:54| INFO mulmc_sld finished [took 61.4168s]
|
||||
06/11/23 06:41:56| INFO mulne_sld finished [took 61.3708s]
|
||||
06/11/23 06:42:00| INFO mul_pacc finished [took 62.6486s]
|
||||
06/11/23 06:44:23| INFO bin_sld finished [took 212.5992s]
|
||||
06/11/23 06:44:23| INFO bin_pacc finished [took 207.5241s]
|
||||
06/11/23 06:44:24| INFO binmc_sld finished [took 212.2794s]
|
||||
06/11/23 06:44:27| INFO binne_sld finished [took 212.8325s]
|
||||
06/11/23 06:44:27| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 217.7909s]
|
||||
06/11/23 06:44:27| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:45:23| INFO ref finished [took 46.6997s]
|
||||
06/11/23 06:45:28| INFO atc_mc finished [took 50.6417s]
|
||||
06/11/23 06:45:30| INFO mul_sld finished [took 61.5352s]
|
||||
06/11/23 06:45:31| INFO mul_pacc finished [took 55.9055s]
|
||||
06/11/23 06:45:31| INFO mulmc_sld finished [took 60.6608s]
|
||||
06/11/23 06:45:33| INFO mulne_sld finished [took 60.1616s]
|
||||
06/11/23 06:48:01| INFO bin_pacc finished [took 207.7543s]
|
||||
06/11/23 06:48:02| INFO bin_sld finished [took 213.7056s]
|
||||
06/11/23 06:48:03| INFO binmc_sld finished [took 213.7901s]
|
||||
06/11/23 06:48:04| INFO binne_sld finished [took 212.4421s]
|
||||
06/11/23 06:48:04| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 217.4465s]
|
||||
06/11/23 06:48:04| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 06:48:06| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:07| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:09| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:11| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 06:48:13| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 06:48:49| INFO ref finished [took 36.4085s]
|
||||
06/11/23 06:48:53| INFO atc_mc finished [took 39.1380s]
|
||||
06/11/23 06:48:54| INFO mulmc_sld finished [took 46.0254s]
|
||||
06/11/23 06:48:55| INFO mulne_sld finished [took 45.1935s]
|
||||
06/11/23 06:49:00| INFO mul_sld finished [took 53.9145s]
|
||||
06/11/23 06:49:00| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 55.9159s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 18:04:06| INFO dataset rcv1_GCAT_9prevs
|
||||
06/11/23 18:04:12| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:04:19| WARNING Method mul_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:21| WARNING Method bin_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:22| WARNING Method mul_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:24| WARNING Method binmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:24| WARNING Method mulmc_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:26| WARNING Method binne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:27| WARNING Method mulne_pacc failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:28| WARNING Method bin_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:04:29| WARNING Method mul_pacc_gs failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:05:10| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1
|
||||
06/11/23 18:05:41| INFO ref finished [took 65.3048s]
|
||||
06/11/23 18:05:43| INFO kfcv finished [took 66.9585s]
|
||||
06/11/23 18:05:45| INFO doc_feat finished [took 56.7504s]
|
||||
06/11/23 18:05:49| INFO mul_cc finished [took 77.6035s]
|
||||
06/11/23 18:05:49| INFO atc_mc finished [took 66.4650s]
|
||||
06/11/23 18:05:52| INFO atc_ne finished [took 65.1035s]
|
||||
06/11/23 18:05:52| WARNING Method bin_sld_gsq failed. Exception: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
|
||||
06/11/23 18:05:56| INFO mul_sld finished [took 101.3427s]
|
||||
06/11/23 18:08:12| INFO bin_sld finished [took 238.6323s]
|
||||
06/11/23 18:08:21| INFO bin_cc finished [took 230.3034s]
|
||||
06/11/23 18:10:59| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00897) [took 402.3046s]
|
||||
06/11/23 18:11:39| INFO mul_sld_gs finished [took 441.7473s]
|
||||
06/11/23 18:11:39| INFO Dataset sample 0.10 of dataset rcv1_GCAT_9prevs finished [took 446.6543s]
|
||||
06/11/23 18:11:39| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:14:11| INFO mulmc_pacc finished [took 140.5240s]
|
||||
06/11/23 18:14:13| INFO kfcv finished [took 108.3325s]
|
||||
06/11/23 18:14:16| INFO doc_feat finished [took 91.1407s]
|
||||
06/11/23 18:14:21| INFO atc_ne finished [took 96.9645s]
|
||||
06/11/23 18:14:22| INFO mul_pacc finished [took 154.9757s]
|
||||
06/11/23 18:14:36| INFO ref finished [took 118.1583s]
|
||||
06/11/23 18:14:37| INFO atc_mc finished [took 118.5016s]
|
||||
06/11/23 18:14:41| INFO mulne_pacc finished [took 157.8831s]
|
||||
06/11/23 18:14:49| INFO mul_cc finished [took 144.8053s]
|
||||
06/11/23 18:14:50| INFO mul_sld finished [took 188.8450s]
|
||||
06/11/23 18:15:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01452) [took 184.0929s]
|
||||
06/11/23 18:16:33| INFO mul_pacc_gs finished [took 258.2234s]
|
||||
06/11/23 18:18:46| INFO binmc_pacc finished [took 417.1372s]
|
||||
06/11/23 18:18:48| INFO bin_pacc finished [took 422.0619s]
|
||||
06/11/23 18:18:52| INFO bin_sld finished [took 431.4426s]
|
||||
06/11/23 18:18:56| INFO binne_pacc finished [took 421.5812s]
|
||||
06/11/23 18:19:02| INFO bin_cc finished [took 402.4673s]
|
||||
06/11/23 18:19:32| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 18:20:26| INFO bin_sld_gsq finished [took 522.0734s]
|
||||
06/11/23 18:21:11| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01038) [took 540.4022s]
|
||||
06/11/23 18:21:44| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00821) [took 600.6611s]
|
||||
06/11/23 18:22:25| INFO mul_sld_gs finished [took 642.1063s]
|
||||
06/11/23 18:24:14| INFO bin_pacc_gs finished [took 723.2605s]
|
||||
06/11/23 18:26:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00816) [took 911.5066s]
|
||||
06/11/23 18:29:56| INFO bin_sld_gs finished [took 1093.4674s]
|
||||
06/11/23 18:29:56| INFO Dataset sample 0.20 of dataset rcv1_GCAT_9prevs finished [took 1096.7184s]
|
||||
06/11/23 18:29:56| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:32:21| INFO ref finished [took 89.3355s]
|
||||
06/11/23 18:32:33| INFO doc_feat finished [took 91.9119s]
|
||||
06/11/23 18:32:35| INFO mulmc_pacc finished [took 147.2084s]
|
||||
06/11/23 18:32:38| INFO mulne_pacc finished [took 137.0643s]
|
||||
06/11/23 18:32:54| INFO atc_mc finished [took 117.6847s]
|
||||
06/11/23 18:32:56| INFO kfcv finished [took 129.8598s]
|
||||
06/11/23 18:33:00| INFO mul_pacc finished [took 174.5769s]
|
||||
06/11/23 18:33:00| INFO mul_sld finished [took 181.1734s]
|
||||
06/11/23 18:33:03| INFO atc_ne finished [took 123.9984s]
|
||||
06/11/23 18:33:09| INFO mul_cc finished [took 148.8635s]
|
||||
06/11/23 18:33:32| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00629) [took 177.7598s]
|
||||
06/11/23 18:34:51| INFO mul_pacc_gs finished [took 256.4186s]
|
||||
06/11/23 18:37:10| INFO bin_pacc finished [took 425.7912s]
|
||||
06/11/23 18:37:12| INFO binmc_pacc finished [took 425.7599s]
|
||||
06/11/23 18:37:14| INFO binne_pacc finished [took 424.0101s]
|
||||
06/11/23 18:37:18| INFO bin_sld finished [took 440.4389s]
|
||||
06/11/23 18:37:22| INFO bin_cc finished [took 407.2413s]
|
||||
06/11/23 18:37:52| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 18:38:51| INFO bin_sld_gsq finished [took 529.6242s]
|
||||
06/11/23 18:39:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00489) [took 541.8062s]
|
||||
06/11/23 18:40:02| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00615) [took 601.7630s]
|
||||
06/11/23 18:40:45| INFO mul_sld_gs finished [took 644.5111s]
|
||||
06/11/23 18:42:37| INFO bin_pacc_gs finished [took 729.3942s]
|
||||
06/11/23 18:45:36| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00490) [took 936.3088s]
|
||||
06/11/23 18:48:37| INFO bin_sld_gs finished [took 1117.0610s]
|
||||
06/11/23 18:48:37| INFO Dataset sample 0.30 of dataset rcv1_GCAT_9prevs finished [took 1120.9681s]
|
||||
06/11/23 18:48:37| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 18:51:02| INFO doc_feat finished [took 79.6380s]
|
||||
06/11/23 18:51:20| INFO mulne_pacc finished [took 144.5625s]
|
||||
06/11/23 18:51:30| INFO mul_sld finished [took 171.1473s]
|
||||
06/11/23 18:51:35| INFO mulmc_pacc finished [took 166.1468s]
|
||||
06/11/23 18:51:39| INFO mul_pacc finished [took 172.9449s]
|
||||
06/11/23 18:51:43| INFO ref finished [took 132.2492s]
|
||||
06/11/23 18:51:45| INFO kfcv finished [took 137.9538s]
|
||||
06/11/23 18:51:52| INFO atc_mc finished [took 137.7185s]
|
||||
06/11/23 18:51:54| INFO atc_ne finished [took 134.1066s]
|
||||
06/11/23 18:51:59| INFO mul_cc finished [took 159.0670s]
|
||||
06/11/23 18:52:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01049) [took 180.3366s]
|
||||
06/11/23 18:53:38| INFO mul_pacc_gs finished [took 266.6075s]
|
||||
06/11/23 18:56:00| INFO bin_sld finished [took 441.9022s]
|
||||
06/11/23 18:56:02| INFO binne_pacc finished [took 431.1354s]
|
||||
06/11/23 18:56:02| INFO binmc_pacc finished [took 434.5268s]
|
||||
06/11/23 18:56:04| INFO bin_pacc finished [took 438.8400s]
|
||||
06/11/23 18:56:07| INFO bin_cc finished [took 412.8827s]
|
||||
06/11/23 18:56:38| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 18:57:38| INFO bin_sld_gsq finished [took 534.9970s]
|
||||
06/11/23 18:58:15| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00762) [took 549.5790s]
|
||||
06/11/23 18:58:58| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00692) [took 616.7506s]
|
||||
06/11/23 18:59:43| INFO mul_sld_gs finished [took 661.6976s]
|
||||
06/11/23 19:01:20| INFO bin_pacc_gs finished [took 735.1934s]
|
||||
06/11/23 19:04:29| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00601) [took 948.3129s]
|
||||
06/11/23 19:07:30| INFO bin_sld_gs finished [took 1129.1432s]
|
||||
06/11/23 19:07:30| INFO Dataset sample 0.40 of dataset rcv1_GCAT_9prevs finished [took 1133.2853s]
|
||||
06/11/23 19:07:30| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 19:10:11| INFO doc_feat finished [took 90.8028s]
|
||||
06/11/23 19:10:12| INFO mul_sld finished [took 159.3725s]
|
||||
06/11/23 19:10:17| INFO atc_mc finished [took 108.3872s]
|
||||
06/11/23 19:10:20| INFO mulmc_pacc finished [took 158.7937s]
|
||||
06/11/23 19:10:27| INFO kfcv finished [took 125.4384s]
|
||||
06/11/23 19:10:32| INFO mul_cc finished [took 134.1449s]
|
||||
06/11/23 19:10:33| INFO atc_ne finished [took 115.0137s]
|
||||
06/11/23 19:10:33| INFO mul_pacc finished [took 173.4398s]
|
||||
06/11/23 19:10:35| INFO ref finished [took 127.6900s]
|
||||
06/11/23 19:10:35| INFO mulne_pacc finished [took 158.1989s]
|
||||
06/11/23 19:11:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00893) [took 181.2645s]
|
||||
06/11/23 19:12:28| INFO mul_pacc_gs finished [took 263.1619s]
|
||||
06/11/23 19:14:45| INFO bin_sld finished [took 432.8401s]
|
||||
06/11/23 19:14:48| INFO bin_pacc finished [took 430.1210s]
|
||||
06/11/23 19:14:54| INFO binmc_pacc finished [took 433.8715s]
|
||||
06/11/23 19:14:58| INFO bin_cc finished [took 405.7688s]
|
||||
06/11/23 19:14:59| INFO binne_pacc finished [took 435.7315s]
|
||||
06/11/23 19:15:29| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 19:16:36| INFO bin_sld_gsq finished [took 539.4078s]
|
||||
06/11/23 19:17:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00831) [took 545.8362s]
|
||||
06/11/23 19:17:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.001, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00797) [took 609.7895s]
|
||||
06/11/23 19:18:32| INFO mul_sld_gs finished [took 657.1765s]
|
||||
06/11/23 19:20:08| INFO bin_pacc_gs finished [took 728.9184s]
|
||||
06/11/23 19:23:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00738) [took 966.8750s]
|
||||
06/11/23 19:26:42| INFO bin_sld_gs finished [took 1148.2428s]
|
||||
06/11/23 19:26:42| INFO Dataset sample 0.50 of dataset rcv1_GCAT_9prevs finished [took 1152.4463s]
|
||||
06/11/23 19:26:43| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 19:29:16| INFO mul_pacc finished [took 142.3375s]
|
||||
06/11/23 19:29:26| INFO doc_feat finished [took 92.0123s]
|
||||
06/11/23 19:29:29| INFO atc_ne finished [took 96.1697s]
|
||||
06/11/23 19:29:32| INFO mul_sld finished [took 164.7852s]
|
||||
06/11/23 19:29:33| INFO ref finished [took 114.3664s]
|
||||
06/11/23 19:29:36| INFO kfcv finished [took 118.4300s]
|
||||
06/11/23 19:29:37| INFO atc_mc finished [took 111.6950s]
|
||||
06/11/23 19:29:37| INFO mul_cc finished [took 127.8860s]
|
||||
06/11/23 19:29:39| INFO mulmc_pacc finished [took 162.5217s]
|
||||
06/11/23 19:29:46| INFO mulne_pacc finished [took 159.7535s]
|
||||
06/11/23 19:30:22| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00832) [took 183.2267s]
|
||||
06/11/23 19:31:42| INFO mul_pacc_gs finished [took 263.2959s]
|
||||
06/11/23 19:33:48| INFO bin_pacc finished [took 415.7355s]
|
||||
06/11/23 19:33:49| INFO binne_pacc finished [took 411.7032s]
|
||||
06/11/23 19:33:49| INFO bin_sld finished [took 423.6935s]
|
||||
06/11/23 19:33:56| INFO binmc_pacc finished [took 422.0731s]
|
||||
06/11/23 19:34:02| INFO bin_cc finished [took 394.8074s]
|
||||
06/11/23 19:34:45| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 19:35:33| INFO bin_sld_gsq finished [took 523.6794s]
|
||||
06/11/23 19:36:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': 'max_conf'} (score=0.00651) [took 539.0149s]
|
||||
06/11/23 19:36:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00646) [took 605.4721s]
|
||||
06/11/23 19:37:37| INFO mul_sld_gs finished [took 647.9998s]
|
||||
06/11/23 19:39:13| INFO bin_pacc_gs finished [took 722.3065s]
|
||||
06/11/23 19:42:14| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00635) [took 926.2548s]
|
||||
06/11/23 19:45:13| INFO bin_sld_gs finished [took 1105.8303s]
|
||||
06/11/23 19:45:13| INFO Dataset sample 0.60 of dataset rcv1_GCAT_9prevs finished [took 1110.5345s]
|
||||
06/11/23 19:45:13| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 19:47:55| INFO mul_pacc finished [took 151.2717s]
|
||||
06/11/23 19:48:01| INFO mul_sld finished [took 164.7303s]
|
||||
06/11/23 19:48:02| INFO doc_feat finished [took 95.7218s]
|
||||
06/11/23 19:48:20| INFO kfcv finished [took 132.6414s]
|
||||
06/11/23 19:48:26| INFO ref finished [took 136.4855s]
|
||||
06/11/23 19:48:27| INFO mulmc_pacc finished [took 180.2510s]
|
||||
06/11/23 19:48:30| INFO mulne_pacc finished [took 173.6996s]
|
||||
06/11/23 19:48:33| INFO atc_mc finished [took 135.5939s]
|
||||
06/11/23 19:48:34| INFO atc_ne finished [took 129.3719s]
|
||||
06/11/23 19:48:35| INFO mul_cc finished [took 153.9587s]
|
||||
06/11/23 19:48:47| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00782) [took 177.0918s]
|
||||
06/11/23 19:50:13| INFO mul_pacc_gs finished [took 262.7047s]
|
||||
06/11/23 19:52:34| INFO bin_pacc finished [took 431.9695s]
|
||||
06/11/23 19:52:36| INFO binmc_pacc finished [took 430.1566s]
|
||||
06/11/23 19:52:43| INFO bin_sld finished [took 446.4452s]
|
||||
06/11/23 19:52:44| INFO bin_cc finished [took 407.8850s]
|
||||
06/11/23 19:52:47| INFO binne_pacc finished [took 438.4423s]
|
||||
06/11/23 19:53:19| WARNING Method mul_sld_gsq failed. Exception: 'function' object has no attribute 'classes_'
|
||||
06/11/23 19:54:09| INFO bin_sld_gsq finished [took 528.9254s]
|
||||
06/11/23 19:54:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.01, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00669) [took 545.8164s]
|
||||
06/11/23 19:55:38| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00814) [took 619.0258s]
|
||||
06/11/23 19:56:21| INFO mul_sld_gs finished [took 661.4303s]
|
||||
06/11/23 19:57:51| INFO bin_pacc_gs finished [took 733.3970s]
|
||||
06/11/23 20:00:54| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00795) [took 935.9973s]
|
||||
06/11/23 20:03:55| INFO bin_sld_gs finished [took 1117.3981s]
|
||||
06/11/23 20:03:55| INFO Dataset sample 0.70 of dataset rcv1_GCAT_9prevs finished [took 1121.8060s]
|
||||
06/11/23 20:03:55| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 20:06:27| INFO mul_sld finished [took 147.0727s]
|
||||
06/11/23 20:06:30| INFO doc_feat finished [took 81.1117s]
|
||||
06/11/23 20:06:48| INFO mul_pacc finished [took 162.2312s]
|
||||
06/11/23 20:07:04| INFO kfcv finished [took 133.4389s]
|
||||
06/11/23 20:07:04| INFO ref finished [took 132.6728s]
|
||||
06/11/23 20:07:05| INFO mulne_pacc finished [took 171.0782s]
|
||||
06/11/23 20:07:08| INFO mulmc_pacc finished [took 179.6909s]
|
||||
06/11/23 20:07:10| INFO atc_mc finished [took 130.5941s]
|
||||
06/11/23 20:07:14| INFO mul_cc finished [took 150.3795s]
|
||||
06/11/23 20:07:15| INFO atc_ne finished [took 131.0309s]
|
||||
06/11/23 20:07:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00813) [took 177.7289s]
|
||||
06/11/23 20:08:49| INFO mul_pacc_gs finished [took 257.9675s]
|
||||
06/11/23 20:10:44| INFO bin_pacc finished [took 399.4800s]
|
||||
06/11/23 21:01:51| INFO bin_pacc_gs finished [took 3446.1854s]
|
||||
06/11/23 21:03:24| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00684) [took 3563.0699s]
|
||||
06/11/23 21:04:07| INFO mul_sld_gs finished [took 3606.0194s]
|
||||
06/11/23 21:08:24| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00519) [took 3863.9570s]
|
||||
06/11/23 21:11:26| INFO bin_sld_gs finished [took 4046.4500s]
|
||||
06/11/23 21:11:26| INFO Dataset sample 0.80 of dataset rcv1_GCAT_9prevs finished [took 4051.2016s]
|
||||
06/11/23 21:11:26| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs started
|
||||
06/11/23 21:11:31| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:32| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:34| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:35| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
|
||||
06/11/23 21:11:36| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:38| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:38| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:40| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:40| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:42| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:42| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:11:44| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 21:11:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 21:12:27| INFO mul_sld finished [took 56.8958s]
|
||||
06/11/23 21:12:32| INFO ref finished [took 44.3311s]
|
||||
06/11/23 21:12:32| INFO doc_feat finished [took 41.1551s]
|
||||
06/11/23 21:12:33| INFO kfcv finished [took 46.1873s]
|
||||
06/11/23 21:12:36| INFO atc_mc finished [took 47.9541s]
|
||||
06/11/23 21:12:37| INFO mul_cc finished [took 51.8838s]
|
||||
06/11/23 21:12:37| INFO atc_ne finished [took 47.4962s]
|
||||
06/11/23 21:16:45| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00843) [took 312.8612s]
|
||||
06/11/23 21:17:24| INFO mul_sld_gs finished [took 351.5693s]
|
||||
06/11/23 21:17:24| INFO Dataset sample 0.90 of dataset rcv1_GCAT_9prevs finished [took 357.7321s]
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
|
|
@ -1,351 +1,351 @@
|
|||
06/11/23 06:50:22| INFO dataset rcv1_MCAT_9prevs
|
||||
06/11/23 06:50:27| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 06:51:29| INFO ref finished [took 47.8430s]
|
||||
06/11/23 06:51:34| INFO atc_mc finished [took 51.2418s]
|
||||
06/11/23 06:51:36| INFO mul_pacc finished [took 56.8770s]
|
||||
06/11/23 06:52:00| INFO mulne_sld finished [took 85.8579s]
|
||||
06/11/23 06:52:00| INFO mul_sld finished [took 90.6401s]
|
||||
06/11/23 06:52:12| INFO mulmc_sld finished [took 100.3728s]
|
||||
06/11/23 06:54:15| INFO bin_pacc finished [took 217.8843s]
|
||||
06/11/23 06:54:15| INFO bin_sld finished [took 226.6925s]
|
||||
06/11/23 06:54:17| INFO binne_sld finished [took 224.5785s]
|
||||
06/11/23 06:54:17| INFO binmc_sld finished [took 226.9490s]
|
||||
06/11/23 06:54:17| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 229.9256s]
|
||||
06/11/23 06:54:17| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 06:55:14| INFO ref finished [took 46.7323s]
|
||||
06/11/23 06:55:20| INFO atc_mc finished [took 51.0126s]
|
||||
06/11/23 06:55:22| INFO mul_pacc finished [took 55.8357s]
|
||||
06/11/23 06:55:23| INFO mulmc_sld finished [took 62.0464s]
|
||||
06/11/23 06:55:24| INFO mul_sld finished [took 64.8106s]
|
||||
06/11/23 06:55:25| INFO mulne_sld finished [took 61.6750s]
|
||||
06/11/23 06:57:56| INFO bin_pacc finished [took 210.8901s]
|
||||
06/11/23 06:57:56| INFO bin_sld finished [took 217.3461s]
|
||||
06/11/23 06:57:57| INFO binmc_sld finished [took 216.6599s]
|
||||
06/11/23 06:58:00| INFO binne_sld finished [took 216.9668s]
|
||||
06/11/23 06:58:00| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 222.3450s]
|
||||
06/11/23 06:58:00| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 06:58:57| INFO ref finished [took 47.5989s]
|
||||
06/11/23 06:59:02| INFO atc_mc finished [took 51.5080s]
|
||||
06/11/23 06:59:04| INFO mul_pacc finished [took 56.1671s]
|
||||
06/11/23 06:59:09| INFO mulmc_sld finished [took 65.0229s]
|
||||
06/11/23 06:59:10| INFO mul_sld finished [took 68.8366s]
|
||||
06/11/23 06:59:11| INFO mulne_sld finished [took 65.2964s]
|
||||
06/11/23 07:01:39| INFO bin_pacc finished [took 212.3570s]
|
||||
06/11/23 07:01:40| INFO bin_sld finished [took 219.3886s]
|
||||
06/11/23 07:01:42| INFO binmc_sld finished [took 219.1471s]
|
||||
06/11/23 07:01:43| INFO binne_sld finished [took 218.3714s]
|
||||
06/11/23 07:01:43| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 223.2305s]
|
||||
06/11/23 07:01:43| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:02:40| INFO ref finished [took 47.3513s]
|
||||
06/11/23 07:02:45| INFO atc_mc finished [took 51.3858s]
|
||||
06/11/23 07:02:47| INFO mul_pacc finished [took 56.3829s]
|
||||
06/11/23 07:02:50| INFO mul_sld finished [took 64.9257s]
|
||||
06/11/23 07:02:50| INFO mulmc_sld finished [took 63.6515s]
|
||||
06/11/23 07:02:52| INFO mulne_sld finished [took 63.8008s]
|
||||
06/11/23 07:05:22| INFO bin_pacc finished [took 211.8418s]
|
||||
06/11/23 07:05:22| INFO binmc_sld finished [took 216.4950s]
|
||||
06/11/23 07:05:22| INFO bin_sld finished [took 218.2730s]
|
||||
06/11/23 07:05:25| INFO binne_sld finished [took 217.6016s]
|
||||
06/11/23 07:05:25| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 222.4416s]
|
||||
06/11/23 07:05:25| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:06:22| INFO ref finished [took 47.3783s]
|
||||
06/11/23 07:06:27| INFO atc_mc finished [took 51.1924s]
|
||||
06/11/23 07:06:30| INFO mul_pacc finished [took 56.3115s]
|
||||
06/11/23 07:06:34| INFO mul_sld finished [took 66.6559s]
|
||||
06/11/23 07:06:34| INFO mulmc_sld finished [took 65.2448s]
|
||||
06/11/23 07:06:37| INFO mulne_sld finished [took 65.6557s]
|
||||
06/11/23 07:09:03| INFO binmc_sld finished [took 214.4549s]
|
||||
06/11/23 07:09:03| INFO bin_sld finished [took 216.8097s]
|
||||
06/11/23 07:09:04| INFO bin_pacc finished [took 211.9484s]
|
||||
06/11/23 07:09:06| INFO binne_sld finished [took 215.5010s]
|
||||
06/11/23 07:09:06| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 220.4788s]
|
||||
06/11/23 07:09:06| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:10:03| INFO ref finished [took 47.0882s]
|
||||
06/11/23 07:10:08| INFO atc_mc finished [took 51.1826s]
|
||||
06/11/23 07:10:10| INFO mul_pacc finished [took 55.8766s]
|
||||
06/11/23 07:10:14| INFO mulmc_sld finished [took 64.7175s]
|
||||
06/11/23 07:10:15| INFO mul_sld finished [took 67.2892s]
|
||||
06/11/23 07:10:17| INFO mulne_sld finished [took 64.9305s]
|
||||
06/11/23 07:12:40| INFO bin_pacc finished [took 207.6921s]
|
||||
06/11/23 07:12:41| INFO binmc_sld finished [took 212.3821s]
|
||||
06/11/23 07:12:41| INFO bin_sld finished [took 214.5241s]
|
||||
06/11/23 07:12:43| INFO binne_sld finished [took 212.5115s]
|
||||
06/11/23 07:12:43| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 217.3597s]
|
||||
06/11/23 07:12:43| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:13:39| INFO ref finished [took 46.5374s]
|
||||
06/11/23 07:13:45| INFO atc_mc finished [took 51.0121s]
|
||||
06/11/23 07:13:47| INFO mul_pacc finished [took 55.4950s]
|
||||
06/11/23 07:13:52| INFO mulmc_sld finished [took 64.7651s]
|
||||
06/11/23 07:13:52| INFO mul_sld finished [took 67.0632s]
|
||||
06/11/23 07:13:54| INFO mulne_sld finished [took 65.2533s]
|
||||
06/11/23 07:16:18| INFO bin_pacc finished [took 207.9541s]
|
||||
06/11/23 07:16:19| INFO bin_sld finished [took 214.6495s]
|
||||
06/11/23 07:16:19| INFO binmc_sld finished [took 213.2167s]
|
||||
06/11/23 07:16:24| INFO binne_sld finished [took 215.5646s]
|
||||
06/11/23 07:16:24| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 220.4851s]
|
||||
06/11/23 07:16:24| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:17:20| INFO ref finished [took 46.7655s]
|
||||
06/11/23 07:17:25| INFO atc_mc finished [took 50.9430s]
|
||||
06/11/23 07:17:27| INFO mul_pacc finished [took 55.4948s]
|
||||
06/11/23 07:17:44| INFO mul_sld finished [took 78.5002s]
|
||||
06/11/23 07:17:46| INFO mulmc_sld finished [took 78.7519s]
|
||||
06/11/23 07:17:48| INFO mulne_sld finished [took 78.4293s]
|
||||
06/11/23 07:19:59| INFO bin_pacc finished [took 208.5200s]
|
||||
06/11/23 07:20:02| INFO bin_sld finished [took 216.9046s]
|
||||
06/11/23 07:20:03| INFO binmc_sld finished [took 216.2736s]
|
||||
06/11/23 07:20:03| INFO binne_sld finished [took 214.9573s]
|
||||
06/11/23 07:20:03| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 219.7592s]
|
||||
06/11/23 07:20:03| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:20:05| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:06| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:08| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:10| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:12| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 07:20:48| INFO ref finished [took 36.6985s]
|
||||
06/11/23 07:20:52| INFO atc_mc finished [took 39.8292s]
|
||||
06/11/23 07:20:55| INFO mulmc_sld finished [took 48.0943s]
|
||||
06/11/23 07:20:56| INFO mul_sld finished [took 50.2138s]
|
||||
06/11/23 07:20:57| INFO mulne_sld finished [took 47.9755s]
|
||||
06/11/23 07:20:57| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 53.5645s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 21:20:10| INFO dataset rcv1_MCAT_9prevs
|
||||
06/11/23 21:20:18| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 21:23:12| INFO doc_feat finished [took 81.2849s]
|
||||
06/11/23 21:23:21| INFO mul_pacc finished [took 168.3242s]
|
||||
06/11/23 21:23:30| INFO mulmc_pacc finished [took 173.2730s]
|
||||
06/11/23 21:23:35| INFO atc_mc finished [took 115.3803s]
|
||||
06/11/23 21:23:41| INFO ref finished [took 125.5611s]
|
||||
06/11/23 21:23:41| INFO kfcv finished [took 136.3040s]
|
||||
06/11/23 21:23:51| INFO mulne_pacc finished [took 185.3346s]
|
||||
06/11/23 21:23:58| INFO atc_ne finished [took 129.7752s]
|
||||
06/11/23 21:23:59| INFO mul_cc finished [took 164.3501s]
|
||||
06/11/23 21:24:26| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.02036) [took 203.9839s]
|
||||
06/11/23 21:24:32| INFO mul_sld finished [took 249.6979s]
|
||||
06/11/23 21:25:50| INFO mul_pacc_gs finished [took 287.7634s]
|
||||
06/11/23 21:28:08| INFO binne_pacc finished [took 443.1314s]
|
||||
06/11/23 21:28:11| INFO bin_cc finished [took 427.7416s]
|
||||
06/11/23 21:28:26| INFO bin_pacc finished [took 475.7859s]
|
||||
06/11/23 21:28:28| INFO binmc_pacc finished [took 472.2702s]
|
||||
06/11/23 21:28:33| INFO bin_sld finished [took 492.0457s]
|
||||
06/11/23 21:29:19| INFO mul_sld_gsq finished [took 529.8190s]
|
||||
06/11/23 21:29:26| INFO bin_sld_gsq finished [took 539.2552s]
|
||||
06/11/23 21:30:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00591) [took 573.3773s]
|
||||
06/11/23 21:31:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00754) [took 661.4704s]
|
||||
06/11/23 21:32:10| INFO mul_sld_gs finished [took 704.6441s]
|
||||
06/11/23 21:33:40| INFO bin_pacc_gs finished [took 763.3541s]
|
||||
06/11/23 21:36:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00760) [took 965.4559s]
|
||||
06/11/23 21:39:31| INFO bin_sld_gs finished [took 1146.5622s]
|
||||
06/11/23 21:39:31| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 1152.1700s]
|
||||
06/11/23 21:39:31| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 21:42:13| INFO doc_feat finished [took 88.9970s]
|
||||
06/11/23 21:42:24| INFO mul_pacc finished [took 161.9999s]
|
||||
06/11/23 21:42:31| INFO mulmc_pacc finished [took 159.0109s]
|
||||
06/11/23 21:42:34| INFO mul_sld finished [took 179.5397s]
|
||||
06/11/23 21:42:42| INFO kfcv finished [took 138.3784s]
|
||||
06/11/23 21:42:42| INFO atc_mc finished [took 127.5150s]
|
||||
06/11/23 21:42:45| INFO ref finished [took 133.9163s]
|
||||
06/11/23 21:42:48| INFO mulne_pacc finished [took 170.3191s]
|
||||
06/11/23 21:42:53| INFO mul_cc finished [took 153.9952s]
|
||||
06/11/23 21:42:57| INFO atc_ne finished [took 133.9857s]
|
||||
06/11/23 21:43:07| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01406) [took 179.2817s]
|
||||
06/11/23 21:44:27| INFO mul_pacc_gs finished [took 259.4430s]
|
||||
06/11/23 21:46:57| INFO bin_pacc finished [took 435.9586s]
|
||||
06/11/23 21:47:02| INFO binmc_pacc finished [took 436.7170s]
|
||||
06/11/23 21:47:02| INFO bin_sld finished [took 448.6901s]
|
||||
06/11/23 21:47:03| INFO binne_pacc finished [took 430.3933s]
|
||||
06/11/23 21:47:06| INFO bin_cc finished [took 413.3717s]
|
||||
06/11/23 21:47:44| INFO mul_sld_gsq finished [took 485.8565s]
|
||||
06/11/23 21:48:40| INFO bin_sld_gsq finished [took 542.6385s]
|
||||
06/11/23 21:49:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01029) [took 558.1111s]
|
||||
06/11/23 21:49:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00862) [took 617.7204s]
|
||||
06/11/23 21:50:38| INFO mul_sld_gs finished [took 661.3619s]
|
||||
06/11/23 21:52:31| INFO bin_pacc_gs finished [took 747.8605s]
|
||||
06/11/23 21:55:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00631) [took 947.6305s]
|
||||
06/11/23 21:58:25| INFO bin_sld_gs finished [took 1128.9705s]
|
||||
06/11/23 21:58:25| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 1133.8038s]
|
||||
06/11/23 21:58:25| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:01:11| INFO doc_feat finished [took 91.6284s]
|
||||
06/11/23 22:01:13| INFO mul_pacc finished [took 157.8979s]
|
||||
06/11/23 22:01:21| INFO ref finished [took 117.5064s]
|
||||
06/11/23 22:01:29| INFO mulmc_pacc finished [took 171.3367s]
|
||||
06/11/23 22:01:34| INFO kfcv finished [took 138.8623s]
|
||||
06/11/23 22:01:44| INFO atc_ne finished [took 127.4515s]
|
||||
06/11/23 22:01:45| INFO mulne_pacc finished [took 175.7659s]
|
||||
06/11/23 22:01:45| INFO atc_mc finished [took 134.5717s]
|
||||
06/11/23 22:01:47| INFO mul_sld finished [took 198.7132s]
|
||||
06/11/23 22:01:53| INFO mul_cc finished [took 156.7010s]
|
||||
06/11/23 22:01:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00920) [took 169.8061s]
|
||||
06/11/23 22:03:15| INFO mul_pacc_gs finished [took 248.7885s]
|
||||
06/11/23 22:05:47| INFO bin_pacc finished [took 433.9454s]
|
||||
06/11/23 22:05:52| INFO binmc_pacc finished [took 435.7566s]
|
||||
06/11/23 22:05:55| INFO binne_pacc finished [took 432.5216s]
|
||||
06/11/23 22:06:02| INFO bin_sld finished [took 455.4425s]
|
||||
06/11/23 22:06:03| INFO bin_cc finished [took 409.9712s]
|
||||
06/11/23 22:06:43| INFO mul_sld_gsq finished [took 490.7571s]
|
||||
06/11/23 22:07:34| INFO bin_sld_gsq finished [took 542.4371s]
|
||||
06/11/23 22:08:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00585) [took 557.7911s]
|
||||
06/11/23 22:08:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 598.8338s]
|
||||
06/11/23 22:09:12| INFO mul_sld_gs finished [took 641.4050s]
|
||||
06/11/23 22:11:15| INFO bin_pacc_gs finished [took 742.8423s]
|
||||
06/11/23 22:14:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00443) [took 940.7448s]
|
||||
06/11/23 22:17:12| INFO bin_sld_gs finished [took 1122.5660s]
|
||||
06/11/23 22:17:12| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 1126.9865s]
|
||||
06/11/23 22:17:12| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:19:32| INFO ref finished [took 85.6333s]
|
||||
06/11/23 22:19:43| INFO mulmc_pacc finished [took 138.3833s]
|
||||
06/11/23 22:19:44| INFO doc_feat finished [took 84.2844s]
|
||||
06/11/23 22:19:54| INFO atc_ne finished [took 99.6744s]
|
||||
06/11/23 22:19:57| INFO kfcv finished [took 114.5018s]
|
||||
06/11/23 22:19:59| INFO mul_cc finished [took 123.4161s]
|
||||
06/11/23 22:20:05| INFO mul_pacc finished [took 163.4607s]
|
||||
06/11/23 22:20:09| INFO mul_sld finished [took 173.7721s]
|
||||
06/11/23 22:20:16| INFO mulne_pacc finished [took 162.8502s]
|
||||
06/11/23 22:20:16| INFO atc_mc finished [took 124.1504s]
|
||||
06/11/23 22:20:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00596) [took 169.9575s]
|
||||
06/11/23 22:21:55| INFO mul_pacc_gs finished [took 248.8139s]
|
||||
06/11/23 22:24:04| INFO binmc_pacc finished [took 400.7570s]
|
||||
06/11/23 22:24:12| INFO bin_pacc finished [took 411.2454s]
|
||||
06/11/23 22:24:21| INFO binne_pacc finished [took 414.5496s]
|
||||
06/11/23 22:24:21| INFO bin_cc finished [took 389.2880s]
|
||||
06/11/23 22:24:25| INFO bin_sld finished [took 431.6256s]
|
||||
06/11/23 22:25:13| INFO mul_sld_gsq finished [took 474.0621s]
|
||||
06/11/23 22:25:54| INFO bin_sld_gsq finished [took 515.9435s]
|
||||
06/11/23 22:26:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00626) [took 539.2315s]
|
||||
06/11/23 22:27:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00612) [took 594.2222s]
|
||||
06/11/23 22:27:54| INFO mul_sld_gs finished [took 637.0683s]
|
||||
06/11/23 22:29:48| INFO bin_pacc_gs finished [took 725.8952s]
|
||||
06/11/23 22:33:01| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00682) [took 945.7122s]
|
||||
06/11/23 22:36:02| INFO bin_sld_gs finished [took 1126.7133s]
|
||||
06/11/23 22:36:02| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 1130.5566s]
|
||||
06/11/23 22:36:02| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:38:42| INFO doc_feat finished [took 76.3995s]
|
||||
06/11/23 22:39:04| INFO mul_pacc finished [took 170.8108s]
|
||||
06/11/23 22:39:11| INFO mulmc_pacc finished [took 169.1537s]
|
||||
06/11/23 22:39:22| INFO ref finished [took 134.5551s]
|
||||
06/11/23 22:39:23| INFO kfcv finished [took 144.5049s]
|
||||
06/11/23 22:39:28| INFO mul_sld finished [took 201.7112s]
|
||||
06/11/23 22:39:31| INFO atc_ne finished [took 127.5871s]
|
||||
06/11/23 22:39:32| INFO atc_mc finished [took 141.1615s]
|
||||
06/11/23 22:39:33| INFO mulne_pacc finished [took 181.7155s]
|
||||
06/11/23 22:39:34| INFO mul_cc finished [took 156.9505s]
|
||||
06/11/23 22:39:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00848) [took 178.6463s]
|
||||
06/11/23 22:41:02| INFO mul_pacc_gs finished [took 264.1109s]
|
||||
06/11/23 22:43:34| INFO binmc_pacc finished [took 438.9742s]
|
||||
06/11/23 22:43:34| INFO bin_pacc finished [took 442.7005s]
|
||||
06/11/23 22:43:43| INFO bin_sld finished [took 458.4940s]
|
||||
06/11/23 22:43:44| INFO binne_pacc finished [took 443.0455s]
|
||||
06/11/23 22:43:55| INFO bin_cc finished [took 423.6361s]
|
||||
06/11/23 22:44:45| INFO mul_sld_gsq finished [took 514.4586s]
|
||||
06/11/23 22:45:32| INFO bin_sld_gsq finished [took 562.7681s]
|
||||
06/11/23 22:46:12| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00790) [took 574.1156s]
|
||||
06/11/23 22:46:42| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00824) [took 633.5645s]
|
||||
06/11/23 22:47:24| INFO mul_sld_gs finished [took 676.3552s]
|
||||
06/11/23 22:49:27| INFO bin_pacc_gs finished [took 768.3574s]
|
||||
06/11/23 22:52:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00861) [took 979.5729s]
|
||||
06/11/23 22:55:32| INFO bin_sld_gs finished [took 1164.7331s]
|
||||
06/11/23 22:55:32| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 1169.2748s]
|
||||
06/11/23 22:55:32| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:58:47| INFO doc_feat finished [took 112.6375s]
|
||||
06/11/23 22:59:00| INFO kfcv finished [took 150.2412s]
|
||||
06/11/23 22:59:00| INFO mul_pacc finished [took 197.0521s]
|
||||
06/11/23 22:59:06| INFO mul_sld finished [took 209.9482s]
|
||||
06/11/23 22:59:07| INFO mulmc_pacc finished [took 198.8911s]
|
||||
06/11/23 22:59:07| INFO ref finished [took 148.7702s]
|
||||
06/11/23 22:59:16| INFO atc_ne finished [took 143.7730s]
|
||||
06/11/23 22:59:18| INFO atc_mc finished [took 151.2783s]
|
||||
06/11/23 22:59:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01122) [took 190.1694s]
|
||||
06/11/23 22:59:26| INFO mul_cc finished [took 179.0100s]
|
||||
06/11/23 22:59:33| INFO mulne_pacc finished [took 211.9002s]
|
||||
06/11/23 23:00:52| INFO mul_pacc_gs finished [took 283.5718s]
|
||||
06/11/23 23:03:21| INFO bin_sld finished [took 466.9682s]
|
||||
06/11/23 23:03:24| INFO binmc_pacc finished [took 456.9500s]
|
||||
06/11/23 23:03:25| INFO bin_pacc finished [took 464.1421s]
|
||||
06/11/23 23:03:39| INFO bin_cc finished [took 445.8302s]
|
||||
06/11/23 23:03:40| INFO binne_pacc finished [took 466.3427s]
|
||||
06/11/23 23:04:10| INFO mul_sld_gsq finished [took 509.0584s]
|
||||
06/11/23 23:04:56| INFO bin_sld_gsq finished [took 556.7578s]
|
||||
06/11/23 23:05:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01033) [took 581.0899s]
|
||||
06/11/23 23:06:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00791) [took 636.6955s]
|
||||
06/11/23 23:07:00| INFO mul_sld_gs finished [took 682.1829s]
|
||||
06/11/23 23:08:59| INFO bin_pacc_gs finished [took 772.0584s]
|
||||
06/11/23 23:11:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00722) [took 966.7367s]
|
||||
06/11/23 23:14:47| INFO bin_sld_gs finished [took 1150.2138s]
|
||||
06/11/23 23:14:47| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 1155.4582s]
|
||||
06/11/23 23:14:47| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 23:17:29| INFO mulmc_pacc finished [took 140.6592s]
|
||||
06/11/23 23:17:37| INFO doc_feat finished [took 93.5374s]
|
||||
06/11/23 23:17:58| INFO mul_pacc finished [took 176.1101s]
|
||||
06/11/23 23:18:06| INFO mulne_pacc finished [took 168.2578s]
|
||||
06/11/23 23:18:06| INFO ref finished [took 138.9670s]
|
||||
06/11/23 23:18:13| INFO atc_ne finished [took 133.8368s]
|
||||
06/11/23 23:18:13| INFO mul_cc finished [took 156.3809s]
|
||||
06/11/23 23:18:14| INFO atc_mc finished [took 140.7865s]
|
||||
06/11/23 23:18:15| INFO kfcv finished [took 150.8563s]
|
||||
06/11/23 23:18:28| INFO mul_sld finished [took 213.5502s]
|
||||
06/11/23 23:18:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00696) [took 184.7202s]
|
||||
06/11/23 23:20:04| INFO mul_pacc_gs finished [took 271.8620s]
|
||||
06/11/23 23:22:38| INFO binne_pacc finished [took 444.7274s]
|
||||
06/11/23 23:22:39| INFO binmc_pacc finished [took 454.8866s]
|
||||
06/11/23 23:22:39| INFO bin_pacc finished [took 458.6381s]
|
||||
06/11/23 23:22:47| INFO bin_cc finished [took 432.1075s]
|
||||
06/11/23 23:22:54| INFO bin_sld finished [took 480.5003s]
|
||||
06/11/23 23:23:33| INFO mul_sld_gsq finished [took 514.0066s]
|
||||
06/11/23 23:24:13| INFO bin_sld_gsq finished [took 554.7885s]
|
||||
06/11/23 23:24:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00603) [took 574.6463s]
|
||||
06/11/23 23:25:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00528) [took 609.3079s]
|
||||
06/11/23 23:25:51| INFO mul_sld_gs finished [took 654.2885s]
|
||||
06/11/23 23:28:10| INFO bin_pacc_gs finished [took 767.8253s]
|
||||
06/11/23 23:30:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00733) [took 947.2105s]
|
||||
06/11/23 23:33:48| INFO bin_sld_gs finished [took 1132.1309s]
|
||||
06/11/23 23:33:48| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 1140.6743s]
|
||||
06/11/23 23:33:48| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 23:36:55| INFO doc_feat finished [took 101.6311s]
|
||||
06/11/23 23:37:16| INFO atc_ne finished [took 124.5854s]
|
||||
06/11/23 23:37:39| INFO mulne_pacc finished [took 198.5060s]
|
||||
06/11/23 23:37:42| INFO mulmc_pacc finished [took 210.8408s]
|
||||
06/11/23 23:37:43| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01019) [took 194.4422s]
|
||||
06/11/23 23:37:44| INFO mul_pacc finished [took 224.0155s]
|
||||
06/11/23 23:37:44| INFO kfcv finished [took 178.0222s]
|
||||
06/11/23 23:37:47| INFO ref finished [took 176.1278s]
|
||||
06/11/23 23:37:55| INFO atc_mc finished [took 173.0154s]
|
||||
06/11/23 23:37:58| INFO mul_cc finished [took 198.1420s]
|
||||
06/11/23 23:38:10| INFO mul_sld finished [took 258.4898s]
|
||||
06/11/23 23:39:25| INFO mul_pacc_gs finished [took 297.0552s]
|
||||
06/11/23 23:41:55| INFO binmc_pacc finished [took 471.8397s]
|
||||
06/11/23 23:42:06| INFO binne_pacc finished [took 470.6917s]
|
||||
06/11/23 23:42:08| INFO bin_pacc finished [took 490.2025s]
|
||||
06/11/23 23:42:11| INFO bin_sld finished [took 500.3974s]
|
||||
06/11/23 23:42:17| INFO bin_cc finished [took 463.2719s]
|
||||
06/11/23 23:42:33| INFO mul_sld_gsq finished [took 515.9211s]
|
||||
06/11/23 23:43:19| INFO bin_sld_gsq finished [took 563.2792s]
|
||||
06/11/23 23:44:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01110) [took 580.7011s]
|
||||
06/11/23 23:44:33| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00755) [took 638.9055s]
|
||||
06/11/23 23:45:18| INFO mul_sld_gs finished [took 683.7473s]
|
||||
06/11/23 23:47:14| INFO bin_pacc_gs finished [took 769.5136s]
|
||||
06/11/23 23:50:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00653) [took 986.1331s]
|
||||
06/11/23 23:53:23| INFO bin_sld_gs finished [took 1170.3407s]
|
||||
06/11/23 23:53:23| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 1175.4004s]
|
||||
06/11/23 23:53:23| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 23:53:29| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:31| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:32| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:34| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
|
||||
06/11/23 23:53:34| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:36| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:37| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:38| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:39| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:41| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:41| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:43| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:54:33| INFO ref finished [took 46.5615s]
|
||||
06/11/23 23:54:34| INFO doc_feat finished [took 43.4254s]
|
||||
06/11/23 23:54:34| INFO kfcv finished [took 48.7260s]
|
||||
06/11/23 23:54:34| INFO mul_sld finished [took 64.5496s]
|
||||
06/11/23 23:54:38| INFO atc_mc finished [took 49.9172s]
|
||||
06/11/23 23:54:39| INFO atc_ne finished [took 49.8635s]
|
||||
06/11/23 23:54:39| INFO mul_cc finished [took 54.7417s]
|
||||
06/11/23 23:58:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01247) [took 295.7388s]
|
||||
06/11/23 23:59:08| INFO mul_sld_gs finished [took 336.2009s]
|
||||
06/11/23 23:59:08| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 344.1389s]
|
||||
06/11/23 06:50:22| INFO dataset rcv1_MCAT_9prevs
|
||||
06/11/23 06:50:27| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 06:51:29| INFO ref finished [took 47.8430s]
|
||||
06/11/23 06:51:34| INFO atc_mc finished [took 51.2418s]
|
||||
06/11/23 06:51:36| INFO mul_pacc finished [took 56.8770s]
|
||||
06/11/23 06:52:00| INFO mulne_sld finished [took 85.8579s]
|
||||
06/11/23 06:52:00| INFO mul_sld finished [took 90.6401s]
|
||||
06/11/23 06:52:12| INFO mulmc_sld finished [took 100.3728s]
|
||||
06/11/23 06:54:15| INFO bin_pacc finished [took 217.8843s]
|
||||
06/11/23 06:54:15| INFO bin_sld finished [took 226.6925s]
|
||||
06/11/23 06:54:17| INFO binne_sld finished [took 224.5785s]
|
||||
06/11/23 06:54:17| INFO binmc_sld finished [took 226.9490s]
|
||||
06/11/23 06:54:17| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 229.9256s]
|
||||
06/11/23 06:54:17| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 06:55:14| INFO ref finished [took 46.7323s]
|
||||
06/11/23 06:55:20| INFO atc_mc finished [took 51.0126s]
|
||||
06/11/23 06:55:22| INFO mul_pacc finished [took 55.8357s]
|
||||
06/11/23 06:55:23| INFO mulmc_sld finished [took 62.0464s]
|
||||
06/11/23 06:55:24| INFO mul_sld finished [took 64.8106s]
|
||||
06/11/23 06:55:25| INFO mulne_sld finished [took 61.6750s]
|
||||
06/11/23 06:57:56| INFO bin_pacc finished [took 210.8901s]
|
||||
06/11/23 06:57:56| INFO bin_sld finished [took 217.3461s]
|
||||
06/11/23 06:57:57| INFO binmc_sld finished [took 216.6599s]
|
||||
06/11/23 06:58:00| INFO binne_sld finished [took 216.9668s]
|
||||
06/11/23 06:58:00| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 222.3450s]
|
||||
06/11/23 06:58:00| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 06:58:57| INFO ref finished [took 47.5989s]
|
||||
06/11/23 06:59:02| INFO atc_mc finished [took 51.5080s]
|
||||
06/11/23 06:59:04| INFO mul_pacc finished [took 56.1671s]
|
||||
06/11/23 06:59:09| INFO mulmc_sld finished [took 65.0229s]
|
||||
06/11/23 06:59:10| INFO mul_sld finished [took 68.8366s]
|
||||
06/11/23 06:59:11| INFO mulne_sld finished [took 65.2964s]
|
||||
06/11/23 07:01:39| INFO bin_pacc finished [took 212.3570s]
|
||||
06/11/23 07:01:40| INFO bin_sld finished [took 219.3886s]
|
||||
06/11/23 07:01:42| INFO binmc_sld finished [took 219.1471s]
|
||||
06/11/23 07:01:43| INFO binne_sld finished [took 218.3714s]
|
||||
06/11/23 07:01:43| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 223.2305s]
|
||||
06/11/23 07:01:43| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:02:40| INFO ref finished [took 47.3513s]
|
||||
06/11/23 07:02:45| INFO atc_mc finished [took 51.3858s]
|
||||
06/11/23 07:02:47| INFO mul_pacc finished [took 56.3829s]
|
||||
06/11/23 07:02:50| INFO mul_sld finished [took 64.9257s]
|
||||
06/11/23 07:02:50| INFO mulmc_sld finished [took 63.6515s]
|
||||
06/11/23 07:02:52| INFO mulne_sld finished [took 63.8008s]
|
||||
06/11/23 07:05:22| INFO bin_pacc finished [took 211.8418s]
|
||||
06/11/23 07:05:22| INFO binmc_sld finished [took 216.4950s]
|
||||
06/11/23 07:05:22| INFO bin_sld finished [took 218.2730s]
|
||||
06/11/23 07:05:25| INFO binne_sld finished [took 217.6016s]
|
||||
06/11/23 07:05:25| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 222.4416s]
|
||||
06/11/23 07:05:25| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:06:22| INFO ref finished [took 47.3783s]
|
||||
06/11/23 07:06:27| INFO atc_mc finished [took 51.1924s]
|
||||
06/11/23 07:06:30| INFO mul_pacc finished [took 56.3115s]
|
||||
06/11/23 07:06:34| INFO mul_sld finished [took 66.6559s]
|
||||
06/11/23 07:06:34| INFO mulmc_sld finished [took 65.2448s]
|
||||
06/11/23 07:06:37| INFO mulne_sld finished [took 65.6557s]
|
||||
06/11/23 07:09:03| INFO binmc_sld finished [took 214.4549s]
|
||||
06/11/23 07:09:03| INFO bin_sld finished [took 216.8097s]
|
||||
06/11/23 07:09:04| INFO bin_pacc finished [took 211.9484s]
|
||||
06/11/23 07:09:06| INFO binne_sld finished [took 215.5010s]
|
||||
06/11/23 07:09:06| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 220.4788s]
|
||||
06/11/23 07:09:06| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:10:03| INFO ref finished [took 47.0882s]
|
||||
06/11/23 07:10:08| INFO atc_mc finished [took 51.1826s]
|
||||
06/11/23 07:10:10| INFO mul_pacc finished [took 55.8766s]
|
||||
06/11/23 07:10:14| INFO mulmc_sld finished [took 64.7175s]
|
||||
06/11/23 07:10:15| INFO mul_sld finished [took 67.2892s]
|
||||
06/11/23 07:10:17| INFO mulne_sld finished [took 64.9305s]
|
||||
06/11/23 07:12:40| INFO bin_pacc finished [took 207.6921s]
|
||||
06/11/23 07:12:41| INFO binmc_sld finished [took 212.3821s]
|
||||
06/11/23 07:12:41| INFO bin_sld finished [took 214.5241s]
|
||||
06/11/23 07:12:43| INFO binne_sld finished [took 212.5115s]
|
||||
06/11/23 07:12:43| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 217.3597s]
|
||||
06/11/23 07:12:43| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:13:39| INFO ref finished [took 46.5374s]
|
||||
06/11/23 07:13:45| INFO atc_mc finished [took 51.0121s]
|
||||
06/11/23 07:13:47| INFO mul_pacc finished [took 55.4950s]
|
||||
06/11/23 07:13:52| INFO mulmc_sld finished [took 64.7651s]
|
||||
06/11/23 07:13:52| INFO mul_sld finished [took 67.0632s]
|
||||
06/11/23 07:13:54| INFO mulne_sld finished [took 65.2533s]
|
||||
06/11/23 07:16:18| INFO bin_pacc finished [took 207.9541s]
|
||||
06/11/23 07:16:19| INFO bin_sld finished [took 214.6495s]
|
||||
06/11/23 07:16:19| INFO binmc_sld finished [took 213.2167s]
|
||||
06/11/23 07:16:24| INFO binne_sld finished [took 215.5646s]
|
||||
06/11/23 07:16:24| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 220.4851s]
|
||||
06/11/23 07:16:24| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:17:20| INFO ref finished [took 46.7655s]
|
||||
06/11/23 07:17:25| INFO atc_mc finished [took 50.9430s]
|
||||
06/11/23 07:17:27| INFO mul_pacc finished [took 55.4948s]
|
||||
06/11/23 07:17:44| INFO mul_sld finished [took 78.5002s]
|
||||
06/11/23 07:17:46| INFO mulmc_sld finished [took 78.7519s]
|
||||
06/11/23 07:17:48| INFO mulne_sld finished [took 78.4293s]
|
||||
06/11/23 07:19:59| INFO bin_pacc finished [took 208.5200s]
|
||||
06/11/23 07:20:02| INFO bin_sld finished [took 216.9046s]
|
||||
06/11/23 07:20:03| INFO binmc_sld finished [took 216.2736s]
|
||||
06/11/23 07:20:03| INFO binne_sld finished [took 214.9573s]
|
||||
06/11/23 07:20:03| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 219.7592s]
|
||||
06/11/23 07:20:03| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 07:20:05| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:06| WARNING Method binmc_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:08| WARNING Method binne_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:10| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 07:20:12| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 07:20:48| INFO ref finished [took 36.6985s]
|
||||
06/11/23 07:20:52| INFO atc_mc finished [took 39.8292s]
|
||||
06/11/23 07:20:55| INFO mulmc_sld finished [took 48.0943s]
|
||||
06/11/23 07:20:56| INFO mul_sld finished [took 50.2138s]
|
||||
06/11/23 07:20:57| INFO mulne_sld finished [took 47.9755s]
|
||||
06/11/23 07:20:57| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 53.5645s]
|
||||
----------------------------------------------------------------------------------------------------
|
||||
06/11/23 21:20:10| INFO dataset rcv1_MCAT_9prevs
|
||||
06/11/23 21:20:18| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 21:23:12| INFO doc_feat finished [took 81.2849s]
|
||||
06/11/23 21:23:21| INFO mul_pacc finished [took 168.3242s]
|
||||
06/11/23 21:23:30| INFO mulmc_pacc finished [took 173.2730s]
|
||||
06/11/23 21:23:35| INFO atc_mc finished [took 115.3803s]
|
||||
06/11/23 21:23:41| INFO ref finished [took 125.5611s]
|
||||
06/11/23 21:23:41| INFO kfcv finished [took 136.3040s]
|
||||
06/11/23 21:23:51| INFO mulne_pacc finished [took 185.3346s]
|
||||
06/11/23 21:23:58| INFO atc_ne finished [took 129.7752s]
|
||||
06/11/23 21:23:59| INFO mul_cc finished [took 164.3501s]
|
||||
06/11/23 21:24:26| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'confidence': 'entropy'} (score=0.02036) [took 203.9839s]
|
||||
06/11/23 21:24:32| INFO mul_sld finished [took 249.6979s]
|
||||
06/11/23 21:25:50| INFO mul_pacc_gs finished [took 287.7634s]
|
||||
06/11/23 21:28:08| INFO binne_pacc finished [took 443.1314s]
|
||||
06/11/23 21:28:11| INFO bin_cc finished [took 427.7416s]
|
||||
06/11/23 21:28:26| INFO bin_pacc finished [took 475.7859s]
|
||||
06/11/23 21:28:28| INFO binmc_pacc finished [took 472.2702s]
|
||||
06/11/23 21:28:33| INFO bin_sld finished [took 492.0457s]
|
||||
06/11/23 21:29:19| INFO mul_sld_gsq finished [took 529.8190s]
|
||||
06/11/23 21:29:26| INFO bin_sld_gsq finished [took 539.2552s]
|
||||
06/11/23 21:30:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00591) [took 573.3773s]
|
||||
06/11/23 21:31:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00754) [took 661.4704s]
|
||||
06/11/23 21:32:10| INFO mul_sld_gs finished [took 704.6441s]
|
||||
06/11/23 21:33:40| INFO bin_pacc_gs finished [took 763.3541s]
|
||||
06/11/23 21:36:30| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00760) [took 965.4559s]
|
||||
06/11/23 21:39:31| INFO bin_sld_gs finished [took 1146.5622s]
|
||||
06/11/23 21:39:31| INFO Dataset sample 0.10 of dataset rcv1_MCAT_9prevs finished [took 1152.1700s]
|
||||
06/11/23 21:39:31| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 21:42:13| INFO doc_feat finished [took 88.9970s]
|
||||
06/11/23 21:42:24| INFO mul_pacc finished [took 161.9999s]
|
||||
06/11/23 21:42:31| INFO mulmc_pacc finished [took 159.0109s]
|
||||
06/11/23 21:42:34| INFO mul_sld finished [took 179.5397s]
|
||||
06/11/23 21:42:42| INFO kfcv finished [took 138.3784s]
|
||||
06/11/23 21:42:42| INFO atc_mc finished [took 127.5150s]
|
||||
06/11/23 21:42:45| INFO ref finished [took 133.9163s]
|
||||
06/11/23 21:42:48| INFO mulne_pacc finished [took 170.3191s]
|
||||
06/11/23 21:42:53| INFO mul_cc finished [took 153.9952s]
|
||||
06/11/23 21:42:57| INFO atc_ne finished [took 133.9857s]
|
||||
06/11/23 21:43:07| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.01406) [took 179.2817s]
|
||||
06/11/23 21:44:27| INFO mul_pacc_gs finished [took 259.4430s]
|
||||
06/11/23 21:46:57| INFO bin_pacc finished [took 435.9586s]
|
||||
06/11/23 21:47:02| INFO binmc_pacc finished [took 436.7170s]
|
||||
06/11/23 21:47:02| INFO bin_sld finished [took 448.6901s]
|
||||
06/11/23 21:47:03| INFO binne_pacc finished [took 430.3933s]
|
||||
06/11/23 21:47:06| INFO bin_cc finished [took 413.3717s]
|
||||
06/11/23 21:47:44| INFO mul_sld_gsq finished [took 485.8565s]
|
||||
06/11/23 21:48:40| INFO bin_sld_gsq finished [took 542.6385s]
|
||||
06/11/23 21:49:21| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01029) [took 558.1111s]
|
||||
06/11/23 21:49:54| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00862) [took 617.7204s]
|
||||
06/11/23 21:50:38| INFO mul_sld_gs finished [took 661.3619s]
|
||||
06/11/23 21:52:31| INFO bin_pacc_gs finished [took 747.8605s]
|
||||
06/11/23 21:55:23| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00631) [took 947.6305s]
|
||||
06/11/23 21:58:25| INFO bin_sld_gs finished [took 1128.9705s]
|
||||
06/11/23 21:58:25| INFO Dataset sample 0.20 of dataset rcv1_MCAT_9prevs finished [took 1133.8038s]
|
||||
06/11/23 21:58:25| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:01:11| INFO doc_feat finished [took 91.6284s]
|
||||
06/11/23 22:01:13| INFO mul_pacc finished [took 157.8979s]
|
||||
06/11/23 22:01:21| INFO ref finished [took 117.5064s]
|
||||
06/11/23 22:01:29| INFO mulmc_pacc finished [took 171.3367s]
|
||||
06/11/23 22:01:34| INFO kfcv finished [took 138.8623s]
|
||||
06/11/23 22:01:44| INFO atc_ne finished [took 127.4515s]
|
||||
06/11/23 22:01:45| INFO mulne_pacc finished [took 175.7659s]
|
||||
06/11/23 22:01:45| INFO atc_mc finished [took 134.5717s]
|
||||
06/11/23 22:01:47| INFO mul_sld finished [took 198.7132s]
|
||||
06/11/23 22:01:53| INFO mul_cc finished [took 156.7010s]
|
||||
06/11/23 22:01:56| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00920) [took 169.8061s]
|
||||
06/11/23 22:03:15| INFO mul_pacc_gs finished [took 248.7885s]
|
||||
06/11/23 22:05:47| INFO bin_pacc finished [took 433.9454s]
|
||||
06/11/23 22:05:52| INFO binmc_pacc finished [took 435.7566s]
|
||||
06/11/23 22:05:55| INFO binne_pacc finished [took 432.5216s]
|
||||
06/11/23 22:06:02| INFO bin_sld finished [took 455.4425s]
|
||||
06/11/23 22:06:03| INFO bin_cc finished [took 409.9712s]
|
||||
06/11/23 22:06:43| INFO mul_sld_gsq finished [took 490.7571s]
|
||||
06/11/23 22:07:34| INFO bin_sld_gsq finished [took 542.4371s]
|
||||
06/11/23 22:08:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': None} (score=0.00585) [took 557.7911s]
|
||||
06/11/23 22:08:29| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00589) [took 598.8338s]
|
||||
06/11/23 22:09:12| INFO mul_sld_gs finished [took 641.4050s]
|
||||
06/11/23 22:11:15| INFO bin_pacc_gs finished [took 742.8423s]
|
||||
06/11/23 22:14:10| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00443) [took 940.7448s]
|
||||
06/11/23 22:17:12| INFO bin_sld_gs finished [took 1122.5660s]
|
||||
06/11/23 22:17:12| INFO Dataset sample 0.30 of dataset rcv1_MCAT_9prevs finished [took 1126.9865s]
|
||||
06/11/23 22:17:12| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:19:32| INFO ref finished [took 85.6333s]
|
||||
06/11/23 22:19:43| INFO mulmc_pacc finished [took 138.3833s]
|
||||
06/11/23 22:19:44| INFO doc_feat finished [took 84.2844s]
|
||||
06/11/23 22:19:54| INFO atc_ne finished [took 99.6744s]
|
||||
06/11/23 22:19:57| INFO kfcv finished [took 114.5018s]
|
||||
06/11/23 22:19:59| INFO mul_cc finished [took 123.4161s]
|
||||
06/11/23 22:20:05| INFO mul_pacc finished [took 163.4607s]
|
||||
06/11/23 22:20:09| INFO mul_sld finished [took 173.7721s]
|
||||
06/11/23 22:20:16| INFO mulne_pacc finished [took 162.8502s]
|
||||
06/11/23 22:20:16| INFO atc_mc finished [took 124.1504s]
|
||||
06/11/23 22:20:36| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00596) [took 169.9575s]
|
||||
06/11/23 22:21:55| INFO mul_pacc_gs finished [took 248.8139s]
|
||||
06/11/23 22:24:04| INFO binmc_pacc finished [took 400.7570s]
|
||||
06/11/23 22:24:12| INFO bin_pacc finished [took 411.2454s]
|
||||
06/11/23 22:24:21| INFO binne_pacc finished [took 414.5496s]
|
||||
06/11/23 22:24:21| INFO bin_cc finished [took 389.2880s]
|
||||
06/11/23 22:24:25| INFO bin_sld finished [took 431.6256s]
|
||||
06/11/23 22:25:13| INFO mul_sld_gsq finished [took 474.0621s]
|
||||
06/11/23 22:25:54| INFO bin_sld_gsq finished [took 515.9435s]
|
||||
06/11/23 22:26:41| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00626) [took 539.2315s]
|
||||
06/11/23 22:27:11| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00612) [took 594.2222s]
|
||||
06/11/23 22:27:54| INFO mul_sld_gs finished [took 637.0683s]
|
||||
06/11/23 22:29:48| INFO bin_pacc_gs finished [took 725.8952s]
|
||||
06/11/23 22:33:01| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00682) [took 945.7122s]
|
||||
06/11/23 22:36:02| INFO bin_sld_gs finished [took 1126.7133s]
|
||||
06/11/23 22:36:02| INFO Dataset sample 0.40 of dataset rcv1_MCAT_9prevs finished [took 1130.5566s]
|
||||
06/11/23 22:36:02| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:38:42| INFO doc_feat finished [took 76.3995s]
|
||||
06/11/23 22:39:04| INFO mul_pacc finished [took 170.8108s]
|
||||
06/11/23 22:39:11| INFO mulmc_pacc finished [took 169.1537s]
|
||||
06/11/23 22:39:22| INFO ref finished [took 134.5551s]
|
||||
06/11/23 22:39:23| INFO kfcv finished [took 144.5049s]
|
||||
06/11/23 22:39:28| INFO mul_sld finished [took 201.7112s]
|
||||
06/11/23 22:39:31| INFO atc_ne finished [took 127.5871s]
|
||||
06/11/23 22:39:32| INFO atc_mc finished [took 141.1615s]
|
||||
06/11/23 22:39:33| INFO mulne_pacc finished [took 181.7155s]
|
||||
06/11/23 22:39:34| INFO mul_cc finished [took 156.9505s]
|
||||
06/11/23 22:39:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.00848) [took 178.6463s]
|
||||
06/11/23 22:41:02| INFO mul_pacc_gs finished [took 264.1109s]
|
||||
06/11/23 22:43:34| INFO binmc_pacc finished [took 438.9742s]
|
||||
06/11/23 22:43:34| INFO bin_pacc finished [took 442.7005s]
|
||||
06/11/23 22:43:43| INFO bin_sld finished [took 458.4940s]
|
||||
06/11/23 22:43:44| INFO binne_pacc finished [took 443.0455s]
|
||||
06/11/23 22:43:55| INFO bin_cc finished [took 423.6361s]
|
||||
06/11/23 22:44:45| INFO mul_sld_gsq finished [took 514.4586s]
|
||||
06/11/23 22:45:32| INFO bin_sld_gsq finished [took 562.7681s]
|
||||
06/11/23 22:46:12| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00790) [took 574.1156s]
|
||||
06/11/23 22:46:42| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00824) [took 633.5645s]
|
||||
06/11/23 22:47:24| INFO mul_sld_gs finished [took 676.3552s]
|
||||
06/11/23 22:49:27| INFO bin_pacc_gs finished [took 768.3574s]
|
||||
06/11/23 22:52:27| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00861) [took 979.5729s]
|
||||
06/11/23 22:55:32| INFO bin_sld_gs finished [took 1164.7331s]
|
||||
06/11/23 22:55:32| INFO Dataset sample 0.50 of dataset rcv1_MCAT_9prevs finished [took 1169.2748s]
|
||||
06/11/23 22:55:32| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 22:58:47| INFO doc_feat finished [took 112.6375s]
|
||||
06/11/23 22:59:00| INFO kfcv finished [took 150.2412s]
|
||||
06/11/23 22:59:00| INFO mul_pacc finished [took 197.0521s]
|
||||
06/11/23 22:59:06| INFO mul_sld finished [took 209.9482s]
|
||||
06/11/23 22:59:07| INFO mulmc_pacc finished [took 198.8911s]
|
||||
06/11/23 22:59:07| INFO ref finished [took 148.7702s]
|
||||
06/11/23 22:59:16| INFO atc_ne finished [took 143.7730s]
|
||||
06/11/23 22:59:18| INFO atc_mc finished [took 151.2783s]
|
||||
06/11/23 22:59:19| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01122) [took 190.1694s]
|
||||
06/11/23 22:59:26| INFO mul_cc finished [took 179.0100s]
|
||||
06/11/23 22:59:33| INFO mulne_pacc finished [took 211.9002s]
|
||||
06/11/23 23:00:52| INFO mul_pacc_gs finished [took 283.5718s]
|
||||
06/11/23 23:03:21| INFO bin_sld finished [took 466.9682s]
|
||||
06/11/23 23:03:24| INFO binmc_pacc finished [took 456.9500s]
|
||||
06/11/23 23:03:25| INFO bin_pacc finished [took 464.1421s]
|
||||
06/11/23 23:03:39| INFO bin_cc finished [took 445.8302s]
|
||||
06/11/23 23:03:40| INFO binne_pacc finished [took 466.3427s]
|
||||
06/11/23 23:04:10| INFO mul_sld_gsq finished [took 509.0584s]
|
||||
06/11/23 23:04:56| INFO bin_sld_gsq finished [took 556.7578s]
|
||||
06/11/23 23:05:48| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'confidence': None} (score=0.01033) [took 581.0899s]
|
||||
06/11/23 23:06:14| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.00791) [took 636.6955s]
|
||||
06/11/23 23:07:00| INFO mul_sld_gs finished [took 682.1829s]
|
||||
06/11/23 23:08:59| INFO bin_pacc_gs finished [took 772.0584s]
|
||||
06/11/23 23:11:44| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 100.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00722) [took 966.7367s]
|
||||
06/11/23 23:14:47| INFO bin_sld_gs finished [took 1150.2138s]
|
||||
06/11/23 23:14:47| INFO Dataset sample 0.60 of dataset rcv1_MCAT_9prevs finished [took 1155.4582s]
|
||||
06/11/23 23:14:47| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 23:17:29| INFO mulmc_pacc finished [took 140.6592s]
|
||||
06/11/23 23:17:37| INFO doc_feat finished [took 93.5374s]
|
||||
06/11/23 23:17:58| INFO mul_pacc finished [took 176.1101s]
|
||||
06/11/23 23:18:06| INFO mulne_pacc finished [took 168.2578s]
|
||||
06/11/23 23:18:06| INFO ref finished [took 138.9670s]
|
||||
06/11/23 23:18:13| INFO atc_ne finished [took 133.8368s]
|
||||
06/11/23 23:18:13| INFO mul_cc finished [took 156.3809s]
|
||||
06/11/23 23:18:14| INFO atc_mc finished [took 140.7865s]
|
||||
06/11/23 23:18:15| INFO kfcv finished [took 150.8563s]
|
||||
06/11/23 23:18:28| INFO mul_sld finished [took 213.5502s]
|
||||
06/11/23 23:18:37| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.00696) [took 184.7202s]
|
||||
06/11/23 23:20:04| INFO mul_pacc_gs finished [took 271.8620s]
|
||||
06/11/23 23:22:38| INFO binne_pacc finished [took 444.7274s]
|
||||
06/11/23 23:22:39| INFO binmc_pacc finished [took 454.8866s]
|
||||
06/11/23 23:22:39| INFO bin_pacc finished [took 458.6381s]
|
||||
06/11/23 23:22:47| INFO bin_cc finished [took 432.1075s]
|
||||
06/11/23 23:22:54| INFO bin_sld finished [took 480.5003s]
|
||||
06/11/23 23:23:33| INFO mul_sld_gsq finished [took 514.0066s]
|
||||
06/11/23 23:24:13| INFO bin_sld_gsq finished [took 554.7885s]
|
||||
06/11/23 23:24:57| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.00603) [took 574.6463s]
|
||||
06/11/23 23:25:06| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00528) [took 609.3079s]
|
||||
06/11/23 23:25:51| INFO mul_sld_gs finished [took 654.2885s]
|
||||
06/11/23 23:28:10| INFO bin_pacc_gs finished [took 767.8253s]
|
||||
06/11/23 23:30:43| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00733) [took 947.2105s]
|
||||
06/11/23 23:33:48| INFO bin_sld_gs finished [took 1132.1309s]
|
||||
06/11/23 23:33:48| INFO Dataset sample 0.70 of dataset rcv1_MCAT_9prevs finished [took 1140.6743s]
|
||||
06/11/23 23:33:48| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 23:36:55| INFO doc_feat finished [took 101.6311s]
|
||||
06/11/23 23:37:16| INFO atc_ne finished [took 124.5854s]
|
||||
06/11/23 23:37:39| INFO mulne_pacc finished [took 198.5060s]
|
||||
06/11/23 23:37:42| INFO mulmc_pacc finished [took 210.8408s]
|
||||
06/11/23 23:37:43| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 1000.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'max_conf'} (score=0.01019) [took 194.4422s]
|
||||
06/11/23 23:37:44| INFO mul_pacc finished [took 224.0155s]
|
||||
06/11/23 23:37:44| INFO kfcv finished [took 178.0222s]
|
||||
06/11/23 23:37:47| INFO ref finished [took 176.1278s]
|
||||
06/11/23 23:37:55| INFO atc_mc finished [took 173.0154s]
|
||||
06/11/23 23:37:58| INFO mul_cc finished [took 198.1420s]
|
||||
06/11/23 23:38:10| INFO mul_sld finished [took 258.4898s]
|
||||
06/11/23 23:39:25| INFO mul_pacc_gs finished [took 297.0552s]
|
||||
06/11/23 23:41:55| INFO binmc_pacc finished [took 471.8397s]
|
||||
06/11/23 23:42:06| INFO binne_pacc finished [took 470.6917s]
|
||||
06/11/23 23:42:08| INFO bin_pacc finished [took 490.2025s]
|
||||
06/11/23 23:42:11| INFO bin_sld finished [took 500.3974s]
|
||||
06/11/23 23:42:17| INFO bin_cc finished [took 463.2719s]
|
||||
06/11/23 23:42:33| INFO mul_sld_gsq finished [took 515.9211s]
|
||||
06/11/23 23:43:19| INFO bin_sld_gsq finished [took 563.2792s]
|
||||
06/11/23 23:44:05| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'confidence': 'entropy'} (score=0.01110) [took 580.7011s]
|
||||
06/11/23 23:44:33| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': 'balanced', 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': 'entropy'} (score=0.00755) [took 638.9055s]
|
||||
06/11/23 23:45:18| INFO mul_sld_gs finished [took 683.7473s]
|
||||
06/11/23 23:47:14| INFO bin_pacc_gs finished [took 769.5136s]
|
||||
06/11/23 23:50:19| DEBUG [BinaryQuantifierAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 0.1, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': 'bcts', 'quantifier__exact_train_prev': True, 'confidence': None} (score=0.00653) [took 986.1331s]
|
||||
06/11/23 23:53:23| INFO bin_sld_gs finished [took 1170.3407s]
|
||||
06/11/23 23:53:23| INFO Dataset sample 0.80 of dataset rcv1_MCAT_9prevs finished [took 1175.4004s]
|
||||
06/11/23 23:53:23| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs started
|
||||
06/11/23 23:53:29| WARNING Method bin_sld failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:31| WARNING Method bin_sld_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:32| WARNING Method bin_sld_gsq failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:34| WARNING Method mul_sld_gsq failed. Exception: a must be greater than 0 unless no samples are taken
|
||||
06/11/23 23:53:34| WARNING Method bin_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:36| WARNING Method mul_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:37| WARNING Method binmc_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:38| WARNING Method binne_pacc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:39| WARNING Method mulmc_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:41| WARNING Method mulne_pacc failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:41| WARNING Method bin_pacc_gs failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:53:43| WARNING Method mul_pacc_gs failed. Exception: could not broadcast input array from shape (3,) into shape (4,)
|
||||
06/11/23 23:53:44| WARNING Method bin_cc failed. Exception: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
|
||||
06/11/23 23:54:33| INFO ref finished [took 46.5615s]
|
||||
06/11/23 23:54:34| INFO doc_feat finished [took 43.4254s]
|
||||
06/11/23 23:54:34| INFO kfcv finished [took 48.7260s]
|
||||
06/11/23 23:54:34| INFO mul_sld finished [took 64.5496s]
|
||||
06/11/23 23:54:38| INFO atc_mc finished [took 49.9172s]
|
||||
06/11/23 23:54:39| INFO atc_ne finished [took 49.8635s]
|
||||
06/11/23 23:54:39| INFO mul_cc finished [took 54.7417s]
|
||||
06/11/23 23:58:27| DEBUG [MultiClassAccuracyEstimator] optimization finished: best params {'quantifier__classifier__C': 10.0, 'quantifier__classifier__class_weight': None, 'quantifier__recalib': None, 'quantifier__exact_train_prev': True, 'confidence': 'max_conf'} (score=0.01247) [took 295.7388s]
|
||||
06/11/23 23:59:08| INFO mul_sld_gs finished [took 336.2009s]
|
||||
06/11/23 23:59:08| INFO Dataset sample 0.90 of dataset rcv1_MCAT_9prevs finished [took 344.1389s]
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
|
|
@ -1,40 +1,40 @@
|
|||
[tool.poetry]
|
||||
name = "quacc"
|
||||
version = "0.1.0"
|
||||
description = ""
|
||||
authors = ["Lorenzo Volpi <lorenzo.volpi@outlook.com>"]
|
||||
readme = "README.md"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.11"
|
||||
quapy = "^0.1.7"
|
||||
pandas = "^2.0.3"
|
||||
jinja2 = "^3.1.2"
|
||||
pyyaml = "^6.0.1"
|
||||
logging = "^0.4.9.6"
|
||||
|
||||
[tool.poetry.scripts]
|
||||
main = "quacc.main:main"
|
||||
comp = "quacc.main:estimate_comparison"
|
||||
tohost = "scp_sync:scp_sync_to_host"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.4.0"
|
||||
pylance = "^0.5.9"
|
||||
pytest-mock = "^3.11.1"
|
||||
pytest-cov = "^4.1.0"
|
||||
win11toast = "^0.32"
|
||||
tabulate = "^0.9.0"
|
||||
paramiko = "^3.3.1"
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
addopts = "--cov=quacc --capture=tee-sys"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[virtualenvs]
|
||||
in-project = true
|
||||
|
||||
[tool.poetry]
|
||||
name = "quacc"
|
||||
version = "0.1.0"
|
||||
description = ""
|
||||
authors = ["Lorenzo Volpi <lorenzo.volpi@outlook.com>"]
|
||||
readme = "README.md"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.11"
|
||||
quapy = "^0.1.7"
|
||||
pandas = "^2.0.3"
|
||||
jinja2 = "^3.1.2"
|
||||
pyyaml = "^6.0.1"
|
||||
logging = "^0.4.9.6"
|
||||
|
||||
[tool.poetry.scripts]
|
||||
main = "quacc.main:main"
|
||||
comp = "quacc.main:estimate_comparison"
|
||||
tohost = "scp_sync:scp_sync_to_host"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.4.0"
|
||||
pylance = "^0.5.9"
|
||||
pytest-mock = "^3.11.1"
|
||||
pytest-cov = "^4.1.0"
|
||||
win11toast = "^0.32"
|
||||
tabulate = "^0.9.0"
|
||||
paramiko = "^3.3.1"
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
addopts = "--cov=quacc --capture=tee-sys"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[virtualenvs]
|
||||
in-project = true
|
||||
|
||||
|
|
|
|||
300
quacc/data.py
300
quacc/data.py
|
|
@ -1,150 +1,150 @@
|
|||
import math
|
||||
from typing import List, Optional
|
||||
|
||||
import numpy as np
|
||||
import scipy.sparse as sp
|
||||
from quapy.data import LabelledCollection
|
||||
|
||||
|
||||
# Extended classes
|
||||
#
|
||||
# 0 ~ True 0
|
||||
# 1 ~ False 1
|
||||
# 2 ~ False 0
|
||||
# 3 ~ True 1
|
||||
# _____________________
|
||||
# | | |
|
||||
# | True 0 | False 1 |
|
||||
# |__________|__________|
|
||||
# | | |
|
||||
# | False 0 | True 1 |
|
||||
# |__________|__________|
|
||||
#
|
||||
class ExClassManager:
|
||||
@staticmethod
|
||||
def get_ex(n_classes: int, true_class: int, pred_class: int) -> int:
|
||||
return true_class * n_classes + pred_class
|
||||
|
||||
@staticmethod
|
||||
def get_pred(n_classes: int, ex_class: int) -> int:
|
||||
return ex_class % n_classes
|
||||
|
||||
@staticmethod
|
||||
def get_true(n_classes: int, ex_class: int) -> int:
|
||||
return ex_class // n_classes
|
||||
|
||||
|
||||
class ExtendedCollection(LabelledCollection):
|
||||
def __init__(
|
||||
self,
|
||||
instances: np.ndarray | sp.csr_matrix,
|
||||
labels: np.ndarray,
|
||||
classes: Optional[List] = None,
|
||||
):
|
||||
super().__init__(instances, labels, classes=classes)
|
||||
|
||||
def split_by_pred(self):
|
||||
_ncl = int(math.sqrt(self.n_classes))
|
||||
_indexes = ExtendedCollection._split_index_by_pred(_ncl, self.instances)
|
||||
if isinstance(self.instances, np.ndarray):
|
||||
_instances = [
|
||||
self.instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
|
||||
for ind in _indexes
|
||||
]
|
||||
elif isinstance(self.instances, sp.csr_matrix):
|
||||
_instances = [
|
||||
self.instances[ind]
|
||||
if ind.shape[0] > 0
|
||||
else sp.csr_matrix(np.empty((0, 0), dtype=int))
|
||||
for ind in _indexes
|
||||
]
|
||||
_labels = [
|
||||
np.asarray(
|
||||
[
|
||||
ExClassManager.get_true(_ncl, lbl)
|
||||
for lbl in (self.labels[ind] if len(ind) > 0 else [])
|
||||
],
|
||||
dtype=int,
|
||||
)
|
||||
for ind in _indexes
|
||||
]
|
||||
return [
|
||||
ExtendedCollection(inst, lbl, classes=range(0, _ncl))
|
||||
for (inst, lbl) in zip(_instances, _labels)
|
||||
]
|
||||
|
||||
@classmethod
|
||||
def split_inst_by_pred(
|
||||
cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
|
||||
) -> (List[np.ndarray | sp.csr_matrix], List[float]):
|
||||
_indexes = cls._split_index_by_pred(n_classes, instances)
|
||||
if isinstance(instances, np.ndarray):
|
||||
_instances = [
|
||||
instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
|
||||
for ind in _indexes
|
||||
]
|
||||
elif isinstance(instances, sp.csr_matrix):
|
||||
_instances = [
|
||||
instances[ind]
|
||||
if ind.shape[0] > 0
|
||||
else sp.csr_matrix(np.empty((0, 0), dtype=int))
|
||||
for ind in _indexes
|
||||
]
|
||||
norms = [inst.shape[0] / instances.shape[0] for inst in _instances]
|
||||
return _instances, norms
|
||||
|
||||
@classmethod
|
||||
def _split_index_by_pred(
|
||||
cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
|
||||
) -> List[np.ndarray]:
|
||||
if isinstance(instances, np.ndarray):
|
||||
_pred_label = [np.argmax(inst[-n_classes:], axis=0) for inst in instances]
|
||||
elif isinstance(instances, sp.csr_matrix):
|
||||
_pred_label = [
|
||||
np.argmax(inst[:, -n_classes:].toarray().flatten(), axis=0)
|
||||
for inst in instances
|
||||
]
|
||||
else:
|
||||
raise ValueError("Unsupported matrix format")
|
||||
|
||||
return [
|
||||
np.asarray([j for (j, x) in enumerate(_pred_label) if x == i], dtype=int)
|
||||
for i in range(0, n_classes)
|
||||
]
|
||||
|
||||
@classmethod
|
||||
def extend_instances(
|
||||
cls, instances: np.ndarray | sp.csr_matrix, pred_proba: np.ndarray
|
||||
) -> np.ndarray | sp.csr_matrix:
|
||||
if isinstance(instances, sp.csr_matrix):
|
||||
_pred_proba = sp.csr_matrix(pred_proba)
|
||||
n_x = sp.hstack([instances, _pred_proba])
|
||||
elif isinstance(instances, np.ndarray):
|
||||
n_x = np.concatenate((instances, pred_proba), axis=1)
|
||||
else:
|
||||
raise ValueError("Unsupported matrix format")
|
||||
|
||||
return n_x
|
||||
|
||||
@classmethod
|
||||
def extend_collection(
|
||||
cls,
|
||||
base: LabelledCollection,
|
||||
pred_proba: np.ndarray,
|
||||
):
|
||||
n_classes = base.n_classes
|
||||
|
||||
# n_X = [ X | predicted probs. ]
|
||||
n_x = cls.extend_instances(base.X, pred_proba)
|
||||
|
||||
# n_y = (exptected y, predicted y)
|
||||
pred_proba = pred_proba[:, -n_classes:]
|
||||
preds = np.argmax(pred_proba, axis=-1)
|
||||
n_y = np.asarray(
|
||||
[
|
||||
ExClassManager.get_ex(n_classes, true_class, pred_class)
|
||||
for (true_class, pred_class) in zip(base.y, preds)
|
||||
]
|
||||
)
|
||||
|
||||
return ExtendedCollection(n_x, n_y, classes=[*range(0, n_classes * n_classes)])
|
||||
import math
|
||||
from typing import List, Optional
|
||||
|
||||
import numpy as np
|
||||
import scipy.sparse as sp
|
||||
from quapy.data import LabelledCollection
|
||||
|
||||
|
||||
# Extended classes
|
||||
#
|
||||
# 0 ~ True 0
|
||||
# 1 ~ False 1
|
||||
# 2 ~ False 0
|
||||
# 3 ~ True 1
|
||||
# _____________________
|
||||
# | | |
|
||||
# | True 0 | False 1 |
|
||||
# |__________|__________|
|
||||
# | | |
|
||||
# | False 0 | True 1 |
|
||||
# |__________|__________|
|
||||
#
|
||||
class ExClassManager:
|
||||
@staticmethod
|
||||
def get_ex(n_classes: int, true_class: int, pred_class: int) -> int:
|
||||
return true_class * n_classes + pred_class
|
||||
|
||||
@staticmethod
|
||||
def get_pred(n_classes: int, ex_class: int) -> int:
|
||||
return ex_class % n_classes
|
||||
|
||||
@staticmethod
|
||||
def get_true(n_classes: int, ex_class: int) -> int:
|
||||
return ex_class // n_classes
|
||||
|
||||
|
||||
class ExtendedCollection(LabelledCollection):
|
||||
def __init__(
|
||||
self,
|
||||
instances: np.ndarray | sp.csr_matrix,
|
||||
labels: np.ndarray,
|
||||
classes: Optional[List] = None,
|
||||
):
|
||||
super().__init__(instances, labels, classes=classes)
|
||||
|
||||
def split_by_pred(self):
|
||||
_ncl = int(math.sqrt(self.n_classes))
|
||||
_indexes = ExtendedCollection._split_index_by_pred(_ncl, self.instances)
|
||||
if isinstance(self.instances, np.ndarray):
|
||||
_instances = [
|
||||
self.instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
|
||||
for ind in _indexes
|
||||
]
|
||||
elif isinstance(self.instances, sp.csr_matrix):
|
||||
_instances = [
|
||||
self.instances[ind]
|
||||
if ind.shape[0] > 0
|
||||
else sp.csr_matrix(np.empty((0, 0), dtype=int))
|
||||
for ind in _indexes
|
||||
]
|
||||
_labels = [
|
||||
np.asarray(
|
||||
[
|
||||
ExClassManager.get_true(_ncl, lbl)
|
||||
for lbl in (self.labels[ind] if len(ind) > 0 else [])
|
||||
],
|
||||
dtype=int,
|
||||
)
|
||||
for ind in _indexes
|
||||
]
|
||||
return [
|
||||
ExtendedCollection(inst, lbl, classes=range(0, _ncl))
|
||||
for (inst, lbl) in zip(_instances, _labels)
|
||||
]
|
||||
|
||||
@classmethod
|
||||
def split_inst_by_pred(
|
||||
cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
|
||||
) -> (List[np.ndarray | sp.csr_matrix], List[float]):
|
||||
_indexes = cls._split_index_by_pred(n_classes, instances)
|
||||
if isinstance(instances, np.ndarray):
|
||||
_instances = [
|
||||
instances[ind] if ind.shape[0] > 0 else np.asarray([], dtype=int)
|
||||
for ind in _indexes
|
||||
]
|
||||
elif isinstance(instances, sp.csr_matrix):
|
||||
_instances = [
|
||||
instances[ind]
|
||||
if ind.shape[0] > 0
|
||||
else sp.csr_matrix(np.empty((0, 0), dtype=int))
|
||||
for ind in _indexes
|
||||
]
|
||||
norms = [inst.shape[0] / instances.shape[0] for inst in _instances]
|
||||
return _instances, norms
|
||||
|
||||
@classmethod
|
||||
def _split_index_by_pred(
|
||||
cls, n_classes: int, instances: np.ndarray | sp.csr_matrix
|
||||
) -> List[np.ndarray]:
|
||||
if isinstance(instances, np.ndarray):
|
||||
_pred_label = [np.argmax(inst[-n_classes:], axis=0) for inst in instances]
|
||||
elif isinstance(instances, sp.csr_matrix):
|
||||
_pred_label = [
|
||||
np.argmax(inst[:, -n_classes:].toarray().flatten(), axis=0)
|
||||
for inst in instances
|
||||
]
|
||||
else:
|
||||
raise ValueError("Unsupported matrix format")
|
||||
|
||||
return [
|
||||
np.asarray([j for (j, x) in enumerate(_pred_label) if x == i], dtype=int)
|
||||
for i in range(0, n_classes)
|
||||
]
|
||||
|
||||
@classmethod
|
||||
def extend_instances(
|
||||
cls, instances: np.ndarray | sp.csr_matrix, pred_proba: np.ndarray
|
||||
) -> np.ndarray | sp.csr_matrix:
|
||||
if isinstance(instances, sp.csr_matrix):
|
||||
_pred_proba = sp.csr_matrix(pred_proba)
|
||||
n_x = sp.hstack([instances, _pred_proba])
|
||||
elif isinstance(instances, np.ndarray):
|
||||
n_x = np.concatenate((instances, pred_proba), axis=1)
|
||||
else:
|
||||
raise ValueError("Unsupported matrix format")
|
||||
|
||||
return n_x
|
||||
|
||||
@classmethod
|
||||
def extend_collection(
|
||||
cls,
|
||||
base: LabelledCollection,
|
||||
pred_proba: np.ndarray,
|
||||
):
|
||||
n_classes = base.n_classes
|
||||
|
||||
# n_X = [ X | predicted probs. ]
|
||||
n_x = cls.extend_instances(base.X, pred_proba)
|
||||
|
||||
# n_y = (exptected y, predicted y)
|
||||
pred_proba = pred_proba[:, -n_classes:]
|
||||
preds = np.argmax(pred_proba, axis=-1)
|
||||
n_y = np.asarray(
|
||||
[
|
||||
ExClassManager.get_ex(n_classes, true_class, pred_class)
|
||||
for (true_class, pred_class) in zip(base.y, preds)
|
||||
]
|
||||
)
|
||||
|
||||
return ExtendedCollection(n_x, n_y, classes=[*range(0, n_classes * n_classes)])
|
||||
|
|
|
|||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue