如何为 scikit 学习随机森林模型设置阈值

Question

看到precision_recall_curve后，如果我想设置阈值=0.4，如何将0.4实现到我的随机森林模型（二元分类）中，对于任何概率<0.4，将其标记为0，对于任何>=0.4，将其标记为1。

from sklearn.ensemble import RandomForestClassifier
  random_forest = RandomForestClassifier(n_estimators=100, oob_score=True, random_state=12)
  random_forest.fit(X_train, y_train)
from sklearn.metrics import accuracy_score
  predicted = random_forest.predict(X_test)
accuracy = accuracy_score(y_test, predicted)

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Answer 1

假设您正在进行二元分类，这很容易：

threshold = 0.4

predicted_proba = random_forest.predict_proba(X_test)
predicted = (predicted_proba [:,1] >= threshold).astype('int')

accuracy = accuracy_score(y_test, predicted)