GridSearchCV没有属性grid.grid_scores _

Question

尝试过的grid.cv_results_没有纠正问题

from sklearn.model_selection
import GridSearchCV
params = {
    'decisiontreeclassifier__max_depth': [1, 2],
    'pipeline-1__clf__C': [0.001, 0.1, 100.0]
}
grid = GridSearchCV(estimator = mv_clf,
    param_grid = params,
    cv = 10,
    scoring = 'roc_auc')
grid.fit(X_train, y_train)
for params, mean_score, scores in grid.grid_scores_:
    print("%0.3f+/-%0.2f %r" %
        (mean_score, scores.std() / 2, params))
#AttributeError: 'GridSearchCV' object has no attribute 'grid_scores_'

尝试用grid.grid_scores_替换grid.cv_results_目的是打印不同的超参数值组合以及通过10倍交叉验证计算出的平均ROC AUC分数]

from sklearn.model_selection
    import GridSearchCV
    params = {
        'decisiontreeclassifier__max_depth': [1, 2],
        'pipeline-1__clf__C': [0.001, 0.1, 100.0]
    }
    grid = GridSearchCV(estimator = mv_clf,
        param_grid = params,
        cv = 10,
        scoring = 'roc_auc')
    grid.fit(X_train, y_train)
    for params, mean_score, scores in grid.grid_scores_:
        print("%0.3f+/-%0.2f %r" %
            (mean_score, scores.std() / 2, params))
    #AttributeError: 'GridSearchCV' object has no attribute 'grid_scores_'

尝试过的grid.cv_results_无法从sklearn.model_selection导入GridSearchCV params = {'decisiontreeclassifier__max_depth'：[1，2]，'pipeline-1__clf__C'：[0.001，0.1，100.0] ...

Answer 1

在最新的scitkit-learn libaray中，grid_scores _

已贬值，并已替换为cv_results _