python randomforestregressor_python – RandomForestRegressor和feature_importances_错误

我正在努力从我的RandomForestRegressor中取出功能重要性,我得到一个：

AttributeError: ‘GridSearchCV’ object has no attribute

‘feature_importances_’.

有谁知道为什么没有属性？根据文档应该存在这个属性？

完整代码：

from sklearn.ensemble import RandomForestRegressor

from sklearn.model_selection import GridSearchCV

#Running a RandomForestRegressor GridSearchCV to tune the model.

parameter_candidates = {

'n_estimators' : [650, 700, 750, 800],

'min_samples_leaf' : [1, 2, 3],

'max_depth' : [10, 11, 12],

'min_samples_split' : [2, 3, 4, 5, 6]

}

RFR_regr = RandomForestRegressor()

CV_RFR_regr = GridSearchCV(estimator=RFR_regr, param_grid=parameter_candidates, n_jobs=5, verbose=2)

CV_RFR_regr.fit(X_train, y_train)

#Predict with testing set

y_pred = CV_RFR_regr.predict(X_test)

#Extract feature importances

importances = CV_RFR_regr.feature_importances_

解决方法:

您正尝试在GridSearchCV对象上使用该属性.它不在那里.您实际需要做的是访问进行网格搜索的估算器.

访问属性：

importances = CV_RFR_regr.best_estimator_.feature_importances_