forked from moreo/QuaPy
removing redundant code
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@ -442,14 +442,6 @@ class PACC(AggregativeProbabilisticQuantifier):
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classes = val_data.classes_
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classes = val_data.classes_
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self.pcc = PCC(self.learner)
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self.pcc = PCC(self.learner)
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# estimate the matrix with entry (i,j) being the estimate of P(yi|yj), that is, the probability that a
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# document that belongs to yj ends up being classified as belonging to yi
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n_classes = len(classes)
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confusion = np.empty(shape=(n_classes, n_classes))
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for i, class_ in enumerate(classes):
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confusion[i] = y_[y == class_].mean(axis=0)
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self.Pte_cond_estim_ = self.getPteCondEstim(classes, y, y_)
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self.Pte_cond_estim_ = self.getPteCondEstim(classes, y, y_)
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return self
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return self
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