gridsearchcv 分类

How to create DataFrame with feature importance from XGBClassifier made by GridSearchCV?

I use GridSearchCV of scikit-learn to find the best parameters for my XGBClassifier model, I use code like below:

grid_params = {
      'n_estimators' : [100, 500, 1000],
      'subsample' : [0.01, 0.05]
}

est = xgb.Classifier()
grid_xgb = GridSearchCV(param_grid = grid_params,
                        estimator = est,
                        scoring = 'roc_auc',
                        cv = 4,
                        verbose = 0)
grid_xgb.fit(X_train, y_train)

print('best estimator:', grid_xgb.best_estimator_)
print('best AUC:', grid_xgb.best_score_)
print('best parameters:', grid_xgb.best_params_)

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