validation.py 文件源码

def test_mat(data, label, model):
    prediction1 = model[0].predict(data)
    prediction2 = model[1].predict(data)
    #return float(np.logical_and(prediction1 == label[:, 0], prediction2 == label[:, 1]).sum()) / len(label)
    label = label[:, 0] * 100 + label[:, 1]
    prediction = prediction1 * 100 + prediction2
    pre, rec, f1, support = metrics.precision_recall_fscore_support(label, prediction)
    f1 = (100*sum(f1[1:] * support[1:])/sum(support[1:]))
    return f1