 Andrea Esuli
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bfbfe08116
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Added classes_ property to all quantifiers.
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2021-05-04 17:09:13 +02:00 |
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Andrea Esuli
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70a3d4bd0f
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Tests for non aggregative and meta methods.
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2021-05-04 12:14:14 +02:00 |
 Alejandro Moreo Fernandez
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1d12e96867
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cleaning
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2021-04-28 11:27:25 +02:00 |
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Alejandro Moreo Fernandez
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8381bce3a8
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more fgsld
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2021-03-11 19:00:40 +01:00 |
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Alejandro Moreo Fernandez
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775417c8eb
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bugfix in PACC
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2021-02-18 13:48:41 +01:00 |
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Alejandro Moreo Fernandez
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854d759dc4
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making everything work like in the wiki
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2021-02-17 18:05:22 +01:00 |
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Alejandro Moreo Fernandez
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70da8f7925
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updating the documentation
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2021-02-16 19:38:52 +01:00 |
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Alejandro Moreo Fernandez
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3aaf57f2f3
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all uci datasets from Pérez-Gállego added, quantification report added
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2021-01-28 18:22:43 +01:00 |
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Alejandro Moreo Fernandez
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e609c262b4
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parallel functionality added to quapy in order to allow for multiprocess parallelization (and not threading) handling quapy's environment variables
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2021-01-27 09:54:41 +01:00 |
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Alejandro Moreo Fernandez
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8a53cfe677
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parallel in threading mode (another)
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2021-01-25 16:46:59 +01:00 |
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Alejandro Moreo Fernandez
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2fda46fc13
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qp.environment was not reachable within Parallel processes; changing backend to threading
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2021-01-25 09:58:39 +01:00 |
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Alejandro Moreo Fernandez
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e7527bd7ed
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bugfix
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2021-01-25 09:02:11 +01:00 |
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Alejandro Moreo Fernandez
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2001c6d852
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running ensembles
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2021-01-25 08:54:10 +01:00 |
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Alejandro Moreo Fernandez
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03cf73aff6
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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
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2021-01-22 18:01:51 +01:00 |
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Alejandro Moreo Fernandez
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54dc2980e6
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creating checkpointdir in fit
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2021-01-22 10:03:08 +01:00 |
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Alejandro Moreo Fernandez
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bf1cc74ba1
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quapy fixed
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2021-01-22 09:58:12 +01:00 |
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Alejandro Moreo Fernandez
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1ba0748b59
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experimental method ave-pool, not working due to the fact that onevsall is aggregative and ave-pool is not
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2021-01-20 17:03:12 +01:00 |
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Alejandro Moreo Fernandez
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99132c8166
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fixing quanet
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2021-01-20 12:35:14 +01:00 |
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Alejandro Moreo Fernandez
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f69eb59eb8
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launching quanet
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2021-01-20 09:01:04 +01:00 |
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Alejandro Moreo Fernandez
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482e4453a8
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refactor of ensembles, launching EPACC with Ptr policy
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2021-01-19 18:26:40 +01:00 |
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Alejandro Moreo Fernandez
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1399125fb8
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adding QuaNet to experiments of Twitter; trying new stuff in 'NewMethods'
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2021-01-18 19:14:04 +01:00 |
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Alejandro Moreo Fernandez
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b30c40b7a0
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some refactor made in order to accomodate OneVsAll to operate with aggregative probabilistic quantifiers; launching OneVsAll(HDy)
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2021-01-18 16:52:19 +01:00 |
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Alejandro Moreo Fernandez
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8ef9e6a633
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bugfix
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2021-01-18 10:53:22 +01:00 |
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Alejandro Moreo Fernandez
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5e64d2588a
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import fixes
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2021-01-15 18:32:32 +01:00 |
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Alejandro Moreo Fernandez
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c5ae2f8b1f
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adding table manager
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2021-01-15 08:33:39 +01:00 |
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Alejandro Moreo Fernandez
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2ec3400d15
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adding tweet sent quant experiments
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2021-01-11 18:31:12 +01:00 |
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Alejandro Moreo Fernandez
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41347b50f9
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cleaning and adding some uci datasets
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2021-01-11 12:55:06 +01:00 |
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Alejandro Moreo Fernandez
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d1b449d2e9
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plot functionality added
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2021-01-07 17:58:48 +01:00 |
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Alejandro Moreo Fernandez
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5894d46b31
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cleaning
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2021-01-06 15:00:48 +01:00 |
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Alejandro Moreo Fernandez
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326a8ab803
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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)
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2021-01-06 14:58:29 +01:00 |
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Alejandro Moreo Fernandez
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d8e2f7556e
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QuaNet added, two examples of TextClassifiers added (CNN, LSTM)
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2020-12-29 20:33:59 +01:00 |
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Alejandro Moreo Fernandez
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7bed93dcbf
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added model selection for quantification
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2020-12-22 17:43:23 +01:00 |
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Alejandro Moreo Fernandez
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71949e9a03
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cleaning
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2020-12-15 15:20:35 +01:00 |
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Alejandro Moreo Fernandez
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c8a1a70c8a
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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
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2020-12-11 19:28:17 +01:00 |
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Alejandro Moreo Fernandez
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e55caf82fd
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merged
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2020-12-10 19:08:22 +01:00 |
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Alejandro Moreo Fernandez
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9bc3a9f28a
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evaluation by artificial prevalence sampling added. New methods added. New util functions added to quapy.functional and quapy.utils
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2020-12-10 19:04:33 +01:00 |
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Alejandro Moreo Fernandez
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2361186a01
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aggregation methods updated
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2020-12-09 12:46:50 +01:00 |
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Alejandro Moreo Fernandez
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9c8d29156c
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aggregative methods adapted. Explicit loss minimization methods (SVMQ, SVMKLD, ...) added and with support to binary or single-label. HDy added
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2020-12-04 19:32:08 +01:00 |
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Alejandro Moreo Fernandez
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a882424eeb
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many aggregative methods added
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2020-12-03 18:12:28 +01:00 |