召回率R,精确率P,精度accuracy,F1计算

一、召回率R,精确率P,精度accuracy,F1定义

二、使用步骤

from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score

#1表示白球，0表示黑球
y_true = [1, 1, 1, 0, 0, 0, 1, 0, 0, 1]
y_pred = [1, 1, 0, 1, 1, 0, 1, 0, 0, 1]

print("acc:", accuracy_score(y_true, y_pred))
print("p:", precision_score(y_true, y_pred))
print("r:", recall_score(y_true, y_pred))
print("f1:", f1_score(y_true, y_pred))

打印输出


例如，图中白球为1，黑球为0
TP = 4,实际的白球，被预测为白球，编号1，2，7，10
FP = 2,实际的黑球，被预测为白球，编号4，5
FN = 1,实际的白球，被预测为黑球，编号3
TN = 3,实际的黑球，被预测为黑球，编号6，8，9

所以
Precision = 4/(4+2) = 2/3 = 0.66667
Recall = 4/(4+1) = 0.8
acc = (4+3)/10 = 0.7

参考

1.https://blog.youkuaiyun.com/lhxez6868/article/details/108150777