1、定义
计算分类结果的准确率
sklearn.metrics.accuracy_score(真实标记集合,分类器对样本集预测的预测值,normalize = [True:比例,False:数量],sample_weight = 样本权重,默认为1)
2、代码
from sklearn.metrics import accuracy_score
y_true=[1,1,1,1,1,0,0,0,0,0]
y_pred=[0,0,1,1,0,0,1,1,0,0]
#准确率
print('准确率','Accuracy Score(normalize=True):',accuracy_score(y_true,y_pred,normalize=True))
#正确分类数量
print('正确分类数量','Accuracy Score(normalize=False):',accuracy_score(y_true,y_pred,normalize=False))
3、结果
准确率 Accuracy Score(normalize=True): 0.5
正确分类数量 Accuracy Score(normalize=False): 5