使用 Sklearn 的 graphviz 时未拟合错误 [英] Not Fitted Error when using Sklearn's graphviz

问题描述

当我尝试使用以下命令导出随机森林图时:

when I am trying to export a random forest graph using the following command:

tree.export_graphviz(rnd_clf, out_file = None, feature_names = X_test[::1])

我收到以下错误:

NotFittedError: This RandomForestClassifier instance is not fitted yet. 
Call 'fit' with appropriate arguments before using this method.

我不明白的是为什么它一直告诉我这个，即使我已经使用以下方法安装了随机森林分类器:

What I don't understand is why it keeps telling me this, even though I have fitted the random forest classifier using:

rnd_clf = RandomForestClassifier(  
             n_estimators=120,
             criterion='gini',
             max_features= None, 
             max_depth = 14 )

rnd_clf.fit(X_train, y_train)

而且它工作得很好.

推荐答案

(只看文档；没有亲身经历)

(Only going by the docs; no personal experience)

您正在尝试使用签名读取的函数绘制一些决策树:

You are trying to plot some DecisionTree, using a function which signature reads:

sklearn.tree.export_graphviz(decision_tree, ...)

但是您正在传递一个RandomForest，它是一个树的集合.

but you are passing a RandomForest, which is an ensemble of trees.

这行不通！

再深入一点，内部代码是此处:

Going deeper, the code internally for this is here:

check_is_fitted(decision_tree, 'tree_')

所以这是要求你的 DecisionTree 的属性 tree_，它存在于 DecisionTreeClassifier.

So this is asking for the attribute tree_ of your DecisionTree, which exists for a DecisionTreeClassifier.

RandomForestClassifier 不存在此属性！因此错误.

This attribute does not exist for a RandomForestClassifier! Therefore the error.

您唯一能做的就是:打印 RandomForest 集成中的每个决策树.为此，您需要遍历 random_forest.estimators_ 以获取底层决策树！

The only thing you can do: print every DecisionTree within your RandomForest ensemble. For this, you need to traverse random_forest.estimators_ to get the underlying decision-trees!

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