122 lines
4.9 KiB
HTML
122 lines
4.9 KiB
HTML
<!DOCTYPE html>
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<html>
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<head>
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<meta charset="UTF-8">
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<title></title>
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<style>
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/* From extension vscode.github */
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/*---------------------------------------------------------------------------------------------
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License. See License.txt in the project root for license information.
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*--------------------------------------------------------------------------------------------*/
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.vscode-dark img[src$=\#gh-light-mode-only],
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.vscode-light img[src$=\#gh-dark-mode-only] {
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display: none;
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}
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</style>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/Microsoft/vscode/extensions/markdown-language-features/media/markdown.css">
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/Microsoft/vscode/extensions/markdown-language-features/media/highlight.css">
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<style>
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body {
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe WPC', 'Segoe UI', system-ui, 'Ubuntu', 'Droid Sans', sans-serif;
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font-size: 14px;
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line-height: 1.6;
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}
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</style>
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<style>
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.task-list-item {
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list-style-type: none;
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}
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.task-list-item-checkbox {
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margin-left: -20px;
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vertical-align: middle;
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pointer-events: none;
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}
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</style>
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</head>
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<body class="vscode-body vscode-light">
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<ul class="contains-task-list">
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere media tabelle</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> plot; 3 tipi (appunti + email + garg)</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> sistemare kfcv baseline</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> aggiungere metodo con CC oltre SLD</p>
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</li>
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<li class="task-list-item enabled">
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<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>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> variare parametro recalibration in SLD</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> fix grafico diagonal</p>
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<ul>
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<li>seaborn example gallery</li>
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</ul>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> varianti recalib: bcts, SLD (provare exact_train_prev=False)</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> vedere cosa usa garg di validation size</p>
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</li>
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<li class="task-list-item enabled">
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<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>
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<ul>
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<li>qp.train_test_split per avere v_train e v_val</li>
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<li>GridSearchQ(
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model: BaseQuantifier,
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param_grid: {
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'classifier__C': np.logspace(-3,3,7),
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'classifier__class_weight': [None, 'balanced'],
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'recalib': [None, 'bcts']
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},
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protocol: UPP(V_val, repeats=1000),
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error = qp.error.mae,
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refit=True,
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timeout=-1,
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n_jobs=-2,
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verbose=True).fit(V_tr)</li>
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</ul>
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</li>
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<li class="task-list-item enabled">
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<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>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> salvare il best score ottenuto da ogni applicazione di GridSearchQ</p>
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<ul>
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<li>nel caso di bin fare media dei due best score</li>
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</ul>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox" checked=""type="checkbox"> import baselines</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox"type="checkbox"> testare anche su imbd</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox"type="checkbox"> plot avg con train prevalence sull'asse x e media su test prevalecne</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox"type="checkbox"> realizzare grid search per task specifico partendo da GridSearchQ</p>
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</li>
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<li class="task-list-item enabled">
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<p><input class="task-list-item-checkbox"type="checkbox"> provare PACC come quantificatore</p>
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</li>
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</ul>
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</body>
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</html> |