4c3790c4553cef37eae4a4e308307f05772579cf,AutoML2015/models/evaluate.py,,evaluate,#Any#Any#Any#,16

Before Change

            Y_optimization_binary[i, label] = 1
        Y_optimization = Y_optimization_binary

    if task_type == "multilabel.classification":
        Y_pred = np.hstack([Y_pred[i][:, 1].reshape((-1, 1))
                             for i in range(len(Y_pred))])

    scoring_func = getattr(libscores, metric)
    csolution, cprediction = libscores.normalize_array(Y_optimization, Y_pred)
    score = scoring_func(csolution, cprediction, task=task_type)

After Change

            Y_optimization_binary[i, label] = 1
        Y_optimization = Y_optimization_binary

    elif task_type == "binary.classification":
        if len(Y_optimization.shape) == 1:
            Y_optimization = convert_to_bin(Y_optimization, 2)

    scoring_func = getattr(libscores, metric)
    csolution, cprediction = libscores.normalize_array(Y_optimization,
                                                       Y_optimization_pred)
    score = scoring_func(csolution, cprediction, task=task_type)

Instances