三种评价函数

from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn.metrics import classification_report

# accuracy_score()
y_true = [0,1,2,3]
y_pred = [0,2,1,3]
print(accuracy_score(y_true=y_true,y_pred=y_pred))


# confusion_matrix()
y_true = [2,0,2,2,0,1]
y_pred = [0,0,2,2,0,2]
print(confusion_matrix(y_true,y_pred))

# classification_report()
y_true = [0,1,2,2,2]
y_pred = [0,0,2,2,1]
print(classification_report(y_true,y_pred))

 

precision = 5 / 8  (预测中/视野)

recall = 5 / 12 (预测中/个数总和)

F1 - score = 2 * precision * recall / (precion + recall)