【发布时间】:2021-06-22 17:41:21
【问题描述】:
我想计算线性回归、随机森林和伯努利的准确率、精确度、召回率和 f1。我想出了以下代码:
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score
y_pred = classifier.predict(X_test)
accuracy = accuracy_score(y_test, y_pred)
print (accuracy)
precision = precision_score(y_test, y_pred, average='macro')
print (precision)
recall = recall_score(y_test, y_pred, average='macro')
print(recall)
f1 = f1_score(y_test, y_pred, average='macro')
print(f1)
如何将其定义为函数,所以我不必编写三遍代码,而是可以应用函数。
【问题讨论】:
标签: python function classification