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rm print
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‎sklearn/ensemble/iforest.py

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@@ -223,8 +223,6 @@ def predict(self, X):
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# Now, to obrain the depth if the tree was fully grown,
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# we have to add the average depth wrt to the number of samples
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# remaining in the leaf:
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print 'depths', depths, depths.shape
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print '_average_path_length(n_samples_leaf)', _average_path_length(n_samples_leaf), _average_path_length(n_samples_leaf).shape
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depths += _average_path_length(n_samples_leaf)
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if not isinstance(self.max_samples, (numbers.Integral, np.integer)):

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