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| def multilabel_confusion_matrix(Y_test, Y_pred): | |
| tp = Y_test.multiply(Y_pred).sum(axis=0) | |
| fp = Y_pred.sum(axis=0) - tp | |
| fn = Y_test.sum(axis=0) - tp | |
| tn = Y_test.shape[0] - tp - fp - fn | |
| return np.array([tn, fp, fn, tp]).T.reshape(-1, 2, 2) |
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