如何在决策树中使用python调用每个类的概率值

Posted 2023-03-12

【中文标题】如何在决策树中使用python调用每个类的概率值

【英文标题】：How to call out probability values for each class using python in decision trees

【发布时间】：2020-02-26 09:56:57

【问题描述】：

如何从预测模型中调出每个类值的概率。

Python 代码：

clf = DecisionTreeClassifier(criterion='gini',
    splitter='best',
    max_depth=None,
    min_samples_split=2,
    min_samples_leaf=1,
    min_weight_fraction_leaf=0.0,
    max_features=None,
    random_state=123,
    max_leaf_nodes=None,
    min_impurity_decrease=0.0,
    min_impurity_split=None,
    class_weight=None,
    presort=False)

# Train Decision Tree Classifer
clf = clf.fit(X_train,y_train)

# Predict the response for test dataset
y_pred = clf.predict(X_test)

# 查看具有预测值的数据集 dtree_gini =pd.DataFrame('实际':y_test, '预测':y_pred) dtree_gini1 = pd.merge(X_test, dtree_gini, left_index=True,right_index=True); dtree_gini1.head(5)

data

desire outcomes

谢谢！

【参考方案1】：

您可以像这样使用函数predict_proba：

y_proba = clf.predict_proba(X_test)