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Multi datasets features into DESlib #266

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Multi datasets features into DESlib #266

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50b496e
Ajout fonctionnel de techniques avec plusieurs datasets.
Feb 26, 2021
e555206
Ajout de l'oracle avec plusieurs datasets.
Feb 27, 2021
0daac6a
Ajout de commentaires, ds_classifiers remplacés par self.
Feb 27, 2021
dc2d050
Ajout de StackedClassifier.
Mar 4, 2021
795a19b
Fix de knorau avec multi-datasets.
Mar 4, 2021
742bffc
Distances ajoutés dans qq techniques, stats à 1 prim ajoutées.
Mar 11, 2021
0f22bec
Merge branch 'multi_datasets' into distances_and_stats
Mar 11, 2021
6835d89
Support des stats à multidatasets, fix avec les stats.
Mar 11, 2021
3a764e4
Segmentation du log.
Mar 12, 2021
9a779a4
Ajout de logs multi-datasets, gestion du cas où il y a 0 désaccords, …
Mar 15, 2021
bdccfc2
Retrait du choix de distances avec fknn.
Mar 22, 2021
58502df
Ajout de KNOP fusionné dans le profil.
Mar 29, 2021
6d3ba91
Fix: quand il y a 0 accord pour une classe.
Jun 24, 2021
7d06fe9
Patch: permet d'avoir 0 ou 1 base par modèle.
Jul 2, 2021
1390e67
PATCH: 1 base permise pour static
Jul 2, 2021
2905fb7
Ajout des tats de la fiabilité de compétence.
Aug 1, 2021
d40452a
Lignes de compétence avec données rendues en pourcentage.
Sep 2, 2021
6b91780
Sanitizing.
Jan 3, 2022
9fd1de4
Retrait du code sur les stats de la SD.
Jan 14, 2022
a71dcd7
Retrait de multiknop.
Jan 14, 2022
2e36290
Sanitazing.
Feb 24, 2022
871abef
Multidatasets tests.
May 17, 2022
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7 changes: 4 additions & 3 deletions deslib/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -803,9 +803,10 @@ def _validate_pool(self):
ValueError
If the pool of classifiers is empty.
"""
if self.n_classifiers_ <= 1:
raise ValueError("n_classifiers must be greater than one, "
"got {}.".format(self.n_classifiers_))
# PATCH: allow 0 or 1 base for the multidatasets model.
#if self.n_classifiers_ <= 1:
# raise ValueError("n_classifiers must be greater than one, "
# "got {}.".format(self.n_classifiers_))

def _check_num_features(self, X):
""" Verify if the number of features (n_features) of X is equals to
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