如何提取 GradientBosstingClassifier 的决策规则 [英] how to extract decision rules of GradientBosstingClassifier

问题描述

我想提取和可视化 scikit-learn GradientBoostingClassifier 的决策规则.如果它只是一个 DecisionTreeClassifier，我会使用 tree.export_graphviz，但 GradientBoostingClassifier 是一组树.我不知道如何对它们使用 export_graphviz.

I want to extract and visualize the decision rules of a scikit-learn GradientBoostingClassifier. If it were just one DecisionTreeClassifier I'd use tree.export_graphviz, but GradientBoostingClassifier is an ensemble of trees. I don't know how I'd use export_graphviz on them.

如果有人知道这样做的方法，那将非常有帮助.

If anyone knows of a way to do so, it will be very helpful.

推荐答案

有人解决了这个问题.您可以使用 clf.estimators_ 检索对应于每个 boosting 阶段的 DecisionTreeRegressor 对象，并调用 export_graphviz 生成树可视化..http://scikit-learn.org/stable/modules/生成/sklearn.ensemble.GradientBoostingClassifier.html"

Someone has solved the problem. "You can use clf.estimators_ to retrieve the DecisionTreeRegressor objects corresponding to each boosting stage and call export_graphviz to generate the tree visualization.. http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html"

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