recommender_wide_and_deep.py 文件源码

def output_confusion_matrix(self, y, y_pred):
        assert y.size == y_pred.size
        print("Actual IDV")
        print(y.value_counts())
        print("Predicted IDV")
        print(y_pred.value_counts())
        print()
        print("Confusion matrix:")
        cmat = pd.crosstab(y_pred, y, rownames=['predictions'], colnames=['actual'])
        print(cmat)
        sys.stdout.flush()
        return cmat

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