ダブルクロスバリデーション（sklearn） - Qiita

from sklearn.datasets import load_diabetes from sklearn.model_selection import GridSearchCV, KFold, cross_val_score from sklearn.pipeline import Pipeline from sklearn.feature_selection import SelectFromModel from sklearn.ensemble import RandomForestRegressor X, y = load_diabetes(return_X_y=True) estimator = RandomForestRegressor() param_grid = {'n_estimators':[10,50,100], 'max_depth':[3,5,10]} tun