"mean_squared_error"的负值； [英] negative value for "mean_squared_error"

问题描述

我正在使用scikit并将mean_squared_error用作评分函数，用于cross_val_score中的模型评估.

I am using scikit and using mean_squared_error as a scoring function for model evaluation in cross_val_score.

rms_score = cross_validation.cross_val_score(model, X, y, cv=20, scoring='mean_squared_error')

我正在使用mean_squared_error，因为这是一个回归问题，并且使用的估计量(模型)为lasso，ridge和elasticNet.

I am using mean_squared_error as it is a regression problem and the estimators (model) used are lasso, ridge and elasticNet.

对于所有这些估计量，我都会得到rms_score作为负值.鉴于y值的差是平方的事实，这怎么可能.

For all these estimators, I am getting rms_score as negative values. How is it possible, given the fact that the differences in y values are squared.

推荐答案

您会得到带有cross_validation.cross_val_score返回的符号翻转的mean_squared_error.为此有一个发行版( https://github.com/scikit-learn /scikit-learn/issues/2439 )，如果这是API或文档错误，则会引起争议.

You get the mean_squared_error with sign flipped returned by cross_validation.cross_val_score. There is an issued opened for that (https://github.com/scikit-learn/scikit-learn/issues/2439), it's controversial if that is an API- or documentation bug.

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