1、定义
Fβ值
F2分数中，召回率的权重高于精确率，而F0.5分数中，精确率的权重高于召回率。
2、代码
y_true=[1,1,1,1,1,0,0,0,0,0]
y_pred=[0,0,1,1,0,0,0,0,0,0]
print('Accuracy Score:',accuracy_score(y_true,y_pred,normalize=True))
print('Precision Score:',precision_score(y_true,y_pred))
print('Recall Score:',recall_score(y_true,y_pred))
print('F1 Score:',f1_score(y_true,y_pred))
print('Fbeta Score(beta=0.001):',fbeta_score(y_true,y_pred,beta=0.001))
print('Fbeta Score(beta=1):',fbeta_score(y_true,y_pred,beta=1))
print('Fbeta Score(beta=10):',fbeta_score(y_true,y_pred,beta=10))
print('Fbeta Score(beta=10000):',fbeta_score(y_true,y_pred,beta=10000))3、结果
y_true=[1,1,1,1,1,0,0,0,0,0]
y_pred=[0,0,1,1,0,0,0,0,0,0]
print('Accuracy Score:',accuracy_score(y_true,y_pred,normalize=True))
print('Precision Score:',precision_score(y_true,y_pred))
print('Recall Score:',recall_score(y_true,y_pred))
print('F1 Score:',f1_score(y_true,y_pred))
print('Fbeta Score(beta=0.001):',fbeta_score(y_true,y_pred,beta=0.001))
print('Fbeta Score(beta=1):',fbeta_score(y_true,y_pred,beta=1))
print('Fbeta Score(beta=10):',fbeta_score(y_true,y_pred,beta=10))
print('Fbeta Score(beta=10000):',fbeta_score(y_true,y_pred,beta=10000))
