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Make Travis happy again
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imblearn/ensemble/easy_ensemble_generalization.py

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@@ -21,7 +21,7 @@
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from ..under_sampling import RandomUnderSampler
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class _EasyEnsembleGeneralization(ClassifierMixin, BaseEnsemble):
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class EasyEnsembleGeneralization(ClassifierMixin, BaseEnsemble):
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"""This classifier generalize the Easy Ensemble algorithm for imbalanced
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datasets.
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def _validate_estimator(self):
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"""Check the estimator and set the base_estimator_ attribute."""
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super(_EasyEnsembleGeneralization, self)._validate_estimator(
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super(EasyEnsembleGeneralization, self)._validate_estimator(
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default=DecisionTreeClassifier())
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def _validate_sampler(self):
@@ -199,10 +199,3 @@ def predict_proba(self, X):
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"""
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check_is_fitted(self, "_voting")
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return self._voting.predict_proba(X)
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# XXX make EasyEnsembleGeneralization to pass sklearn compatibility test
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bases = _EasyEnsembleGeneralization.__mro__
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bases = tuple(x for x in bases if x != MetaEstimatorMixin)
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EasyEnsembleGeneralization = type(
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'EasyEnsembleGeneralization', bases, dict(_EasyEnsembleGeneralization.__dict__))

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