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Fix sklearn requirement
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@@ -98,7 +98,7 @@ class FImdlp(TransformerMixin, BaseEstimator):
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self._update_params(X, y)
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self.X_ = X
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self.y_ = y
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self.efective_min_length = (
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self.efective_min_length_ = (
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self.min_length
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if self.min_length > 1
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else int(self.min_length * X.shape[0])
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@@ -114,7 +114,7 @@ class FImdlp(TransformerMixin, BaseEstimator):
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def _fit_discretizer(self, feature):
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if feature in self.features_:
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self.discretizer_[feature] = CFImdlp(
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min_length=self.efective_min_length,
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min_length=self.efective_min_length_,
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max_depth=self.max_depth,
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max_cuts=self.max_cuts,
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)
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