了解 SciKit Learn CV 验证分数

Question

当运行一个 GridSearchCV 时，我试图理解 cv_validation_scores 的输出。文档没有充分解释这一点。

当我打印 grid_search.grid_scores_ 时，我得到一个包含项目的列表，如下所示：

[mean: 0.60000, std: 0.18002, params: {'tfidf__binary': True, tfidf__ngram_range': (1, 1)....

这是有道理的。但是，当我尝试解压缩 grid_scores 的每个实例时，我得到：

[0] same dictionary as above, makes sense
[1] score for all folds, makes sense
[2] a list that I don't understand, that looks like, "[ 0.75        0.33333333  0.66666667]"

这里报告的分数是多少？

Answer 1

正如我在邮件列表中发布的那样，the documentation 非常清楚：

grid_scores_ : list of named tuples

Contains scores for all parameter combinations in param_grid. Each entry corresponds to one parameter setting. Each named tuple has the attributes:
        parameters, a dict of parameter settings
        mean_validation_score, the mean score over the cross-validation folds
        cv_validation_scores, the list of scores for each fold

这些是交叉验证中每折的分数。

Answer 2

我取消订阅并重新订阅。似乎现在有效

了解 SciKit Learn CV 验证分数

Understand SciKit Learn CV Validation Scores

python

machine-learning

scikit-learn