什么可以替代scikit中的GridSearchCV._grid_scores_?

Ank*_*sal 4 python scikit-learn grid-search sklearn-pandas

由于_grid_scores_方法已被cv_results_取代,我想知道如何输出带有参数和分数的元组?cv_results_提供了得分的数据帧,但是元组输出更易于处理。

请指导我在此新版本的scikit中处理参数和得分值。我计划针对不同范围的参数运行GridSearchCV,然后将它们合并为一个字典。

Viv*_*mar 7

使用for loop从打印结果cv_results_,因为他们在grid_scores_

从文档示例中:

clf = GridSearchCV(init params...)
clf.fit(train data...)

print("Best parameters set found on development set:")
print(clf.best_params_)

print("Grid scores on development set:")
means = clf.cv_results_['mean_test_score']
stds = clf.cv_results_['std_test_score']

#THIS IS WHAT YOU WANT
for mean, std, params in zip(means, stds, clf.cv_results_['params']):
    print("%0.3f (+/-%0.03f) for %r"
          % (mean, std * 2, params))
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