在拟合gridsearchcv(针对随机森林)的过程中,如何打印出每个折叠(训练/测试)集的真实值与预测值(数组)?
代码示例:
parameters = {
'bootstrap': [True, False],
'max_depth': [20,25,30],
'min_samples_leaf': [1,2,3],
'n_estimators': [450,500,550],
'n_jobs': [-1]}
inner_cv = KFold(n_splits=3, shuffle=False, random_state=None)
reg = GridSearchCV(estimator=RandomForestRegressor(),
param_grid=parameters, cv=inner_cv)
reg.fit(X_train, y_train)
另一篇文章建议了这一点,但我觉得应该在试穿时返回:
y_pred = cross_val_predict(reg, X_train, y_train, cv=inner_cv)
* Predicted values of each fold in K-Fold Cross Validation in sklearn