使用Graphviz绘制决策树时，“功能名称长度与功能数量不匹配”错误

Question

我正在尝试使用graphviz可视化决策树，并在尝试绘制决策树时遇到以下错误：

~\AppData\Local\Continuum\anaconda3\lib\site-packages\sklearn\tree\export.py in export_graphviz(decision_tree, out_file, max_depth, feature_names, class_names, label, filled, leaves_parallel, impurity, node_ids, proportion, rotate, rounded, special_characters, precision)
    427                                  "does not match number of features, %d"
    428                                  % (len(feature_names),
--> 429                                     decision_tree.n_features_))
    430 
    431         # The depth of each node for plotting with 'leaf' option

ValueError: Length of feature_names, 225 does not match number of features, 

208

我的代码

dt=DecisionTreeClassifier(class_weight="balanced", min_samples_leaf=30)
fit_decision=dt.fit(X_train_res,y_train_res)
from graphviz import Source
from sklearn import tree
Source( tree.export_graphviz(fit_decision, out_file=None, feature_names=data.columns))

你能告诉我出了什么问题吗？

Answer 1

您的data.columns包含所有功能+标签的名称，因为它没有分为X_train_res和y_train_res。您需要传递X_train_res中的功能名称而不是data.columns以获取确切的功能，否则它还将包含标签。我假设在这种情况下X_train和y_train派生自data。