 Alejandro Moreo Fernandez
|
29db15ae25
|
added DMx and DMy, with a classmethod that returns HDx and HDy respectively
|
2023-11-09 18:13:54 +01:00 |
|
Alejandro Moreo Fernandez
|
c3cf0e2d49
|
adding DistributionMatchingX, the covariate-specific equivalent counterpart of DistributionMatching
|
2023-11-08 16:13:48 +01:00 |
|
Alejandro Moreo Fernandez
|
76cf784844
|
added HDx and an example comparing HDy vs HDx
|
2023-11-08 15:34:17 +01:00 |
|
Alejandro Moreo Fernandez
|
2485117f05
|
adding documentation and adding one new example
|
2023-02-08 19:06:53 +01:00 |
|
Alejandro Moreo Fernandez
|
8b0b9f522a
|
some bugfixes, unittest and minor changes
|
2023-01-16 13:51:29 +01:00 |
Pablo González
|
46e294002f
|
dys implementation
|
2022-07-11 12:21:49 +02:00 |
|
Alejandro Moreo Fernandez
|
eba6fd8123
|
optimization conditional in the prediction function
|
2022-05-26 17:59:23 +02:00 |
|
Alejandro Moreo Fernandez
|
b453c8fcbc
|
first commit protocols
|
2022-05-20 16:48:46 +02:00 |
|
Alejandro Moreo Fernandez
|
ba18d00334
|
trying to figure out how to refactor protocols meaninguflly
|
2021-12-20 11:39:44 +01:00 |
|
Alejandro Moreo Fernandez
|
5deb92b457
|
update doc
|
2021-12-07 17:16:39 +01:00 |
|
Alejandro Moreo Fernandez
|
7468519495
|
testing baselines for lequa
|
2021-11-24 11:20:42 +01:00 |
 Andrea Esuli
|
5b772c7eda
|
Bug fixes on use of classes_. Tests.
|
2021-05-05 17:12:44 +02:00 |
|
Alejandro Moreo Fernandez
|
5e64d2588a
|
import fixes
|
2021-01-15 18:32:32 +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
|
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
|
e55caf82fd
|
merged
|
2020-12-10 19:08:22 +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 |
|
Alejandro Moreo Fernandez
|
9c8d29156c
|
aggregative methods adapted. Explicit loss minimization methods (SVMQ, SVMKLD, ...) added and with support to binary or single-label. HDy added
|
2020-12-04 19:32:08 +01:00 |
|
Alejandro Moreo Fernandez
|
a882424eeb
|
many aggregative methods added
|
2020-12-03 18:12:28 +01:00 |