 Alejandro Moreo Fernandez
|
f2550fdb82
|
full example of training, model selection, and evaluation using the lequa2022 dataset with the new protocols
|
2022-11-04 15:04:36 +01:00 |
|
Alejandro Moreo Fernandez
|
45642ad778
|
lequa as dataset
|
2022-06-01 18:28:59 +02:00 |
|
Alejandro Moreo Fernandez
|
eba6fd8123
|
optimization conditional in the prediction function
|
2022-05-26 17:59:23 +02:00 |
|
Alejandro Moreo Fernandez
|
4bc9d19635
|
many changes, see change log
|
2022-05-25 19:14:33 +02:00 |
|
Alejandro Moreo Fernandez
|
46e3632200
|
ongoing protocols
|
2022-05-23 00:20:08 +02:00 |
|
Alejandro Moreo Fernandez
|
5deb92b457
|
update doc
|
2021-12-07 17:16:39 +01:00 |
|
Alejandro Moreo Fernandez
|
8368c467dc
|
adapting new format
|
2021-11-26 10:57:49 +01:00 |
|
Alejandro Moreo Fernandez
|
238a30520c
|
adapting everything to the new format
|
2021-11-08 18:01:49 +01:00 |
|
Alejandro Moreo Fernandez
|
a7e87e41f8
|
GridSearchQ adapted to work with generator functions and integrated for the baselines of LeQua2022; some tests with SVD
|
2021-10-26 18:41:10 +02:00 |
|
Alejandro Moreo Fernandez
|
be2f54de9c
|
renaming functions to match the app and npp nomenclature; adding npp as an option for GridSearchQ
|
2021-06-16 11:45:40 +02:00 |
|
Alejandro Moreo Fernandez
|
be1fa757d6
|
cleaning
|
2021-05-27 16:56:09 +02:00 |
|
Alejandro Moreo Fernandez
|
731b54c5ba
|
adding natural sampling protocol
|
2021-05-27 16:53:58 +02:00 |
|
Alejandro Moreo Fernandez
|
a2ec72496a
|
adding eval_budget to evaluation functions
|
2021-02-09 11:48:16 +01:00 |
|
Alejandro Moreo Fernandez
|
3aaf57f2f3
|
all uci datasets from Pérez-Gállego added, quantification report added
|
2021-01-28 18:22:43 +01:00 |
|
Alejandro Moreo Fernandez
|
e609c262b4
|
parallel functionality added to quapy in order to allow for multiprocess parallelization (and not threading) handling quapy's environment variables
|
2021-01-27 09:54:41 +01:00 |
|
Alejandro Moreo Fernandez
|
03cf73aff6
|
refactor: methods requiring a val_split can now declare a default value in the __init__ method that will be used in case the fit method is called without specifying the val_split, which now is by default None in the fit, i.e., by default takes the value of the init, that is generally set to 0.4; some uci datasets added; ensembles can now be optimized for quantification, and can be trained on samples of smaller size
|
2021-01-22 18:01:51 +01:00 |
|
Alejandro Moreo Fernandez
|
bf1cc74ba1
|
quapy fixed
|
2021-01-22 09:58:12 +01:00 |
|
Alejandro Moreo Fernandez
|
99132c8166
|
fixing quanet
|
2021-01-20 12:35:14 +01:00 |
|
Alejandro Moreo Fernandez
|
482e4453a8
|
refactor of ensembles, launching EPACC with Ptr policy
|
2021-01-19 18:26:40 +01:00 |
|
Alejandro Moreo Fernandez
|
b30c40b7a0
|
some refactor made in order to accomodate OneVsAll to operate with aggregative probabilistic quantifiers; launching OneVsAll(HDy)
|
2021-01-18 16:52:19 +01:00 |
|
Alejandro Moreo Fernandez
|
5e64d2588a
|
import fixes
|
2021-01-15 18:32:32 +01:00 |
|
Alejandro Moreo Fernandez
|
3c5a53bdec
|
testing quapy via replicating Tweet Quantification experiments
|
2021-01-12 17:39:00 +01:00 |
|
Alejandro Moreo Fernandez
|
3e07feda3c
|
import bug fixed
|
2021-01-12 09:35:49 +01:00 |
|
Alejandro Moreo Fernandez
|
d1b449d2e9
|
plot functionality added
|
2021-01-07 17:58:48 +01:00 |
|
Alejandro Moreo Fernandez
|
326a8ab803
|
added Ensemble methods (methods ALL, ACC, Ptr, DS from Pérez-Gallego et al 2017 and 2019) and some UCI ML datasets used in those articles (only 5 datasets out of 32 they used)
|
2021-01-06 14:58:29 +01:00 |
|
Alejandro Moreo Fernandez
|
7bed93dcbf
|
added model selection for quantification
|
2020-12-22 17:43:23 +01:00 |
|
Alejandro Moreo Fernandez
|
7d6f523e4b
|
uniform sampling added if *prevs is empty
|
2020-12-17 18:17:17 +01:00 |
|
Alejandro Moreo Fernandez
|
c8a1a70c8a
|
refactoring aggregative methods as methods that not only implement 'classify' and 'quantify', but that also implement 'aggregate' and that, by default, have a default implementation of 'quantify' as a pipeline of 'classify' and 'aggregate'; this helps speeding up evaluations A LOT, since the documents can be pre-classified and the samples are carried out across pre-classified values (labels, or posterior probabilities), and thus only aggregate is called many times within the artificial sampling protocol
|
2020-12-11 19:28:17 +01:00 |
|
Alejandro Moreo Fernandez
|
9bc3a9f28a
|
evaluation by artificial prevalence sampling added. New methods added. New util functions added to quapy.functional and quapy.utils
|
2020-12-10 19:04:33 +01:00 |