首页 > 解决方案 > NotFittedError:尚未安装此 BalancedRandomForestClassifier 实例。在使用此方法之前使用适当的参数调用“fit”

问题描述

我很想绘制我的模型,但代码是错误的模型尚未安装。但我安装了模型。有人可以帮我解释为什么我会收到这个错误吗?

我的代码如下;

model = BalancedRandomForestClassifier(n_estimators = 200, random_state = 0, max_depth=6)

model.fit(x_train, y_train)
y_pred_rf = model.predict(x_test)

dot_data = StringIO()
export_graphviz(model, out_file=dot_data,  
            filled=True, rounded=True,
            special_characters=True)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
Image(graph.create_png())

错误如下;

---------------------------------------------------------------------------
NotFittedError                            Traceback (most recent call last)
<ipython-input-57-0036434b9b2c> in <module>
 16 export_graphviz(model, out_file=dot_data,  
 17             filled=True, rounded=True,
 ---> 18             special_characters=True)
 19 graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
 20 Image(graph.create_png())

 /opt/anaconda/envs/env_python/lib/python3.6/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)
 754     """
 755 
 --> 756     check_is_fitted(decision_tree, 'tree_')
 757     own_file = False
 758     return_string = False

 /opt/anaconda/envs/env_python/lib/python3.6/site- 
 packages/sklearn/utils/validation.py in check_is_fitted(estimator, 
 attributes, msg, all_or_any)
 912 
 913     if not all_or_any([hasattr(estimator, attr) for attr in 
 attributes]):
 --> 914         raise NotFittedError(msg % {'name': 
 type(estimator).__name__})
 915 
 916 

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

标签: plotgraphscikit-learnmodelstringio

解决方案


export_graphviz需要一个单一的树模型。因此,当这是一个整体时,您需要遍历树。BalancedRandomForestClassifier暴露estimators_于这种用途。正如 Parthasarathy Subburaj 所提到的,您可以循环其他的estimators_并调用该函数。

这就是说我建议你使用sklearn.tree.plot_tree(...)https ://scikit-learn.org/stable/modules/generated/sklearn.tree.plot_tree.html

它是一个纯 matplotlib 绘图助手,如果您只想获得图像表示而不使用graphviz


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