sklearn.metrics.accuracy_score(y_true, y_pred, normalize=True, sample_weight=None)
normalize:默认值为True,返回正确分类的比例;如果为False,返回正确分类的样本数
>>>import numpy as np
>>>from sklearn.metrics import accuracy_score
>>>y_pred = [0, 2, 1, 3]
>>>y_true = [0, 1, 2, 3]
>>>accuracy_score(y_true, y_pred)
0.5
>>>accuracy_score(y_true, y_pred, normalize=False)
2