Python differences between the methods of the score regression model and the r2 score function

Question

Python differences between the methods of the score regression model and the r2 score function

When building the model, I wanted to compare the values of r2_score () - the coefficient of determination, which I did, but when reading the documentation for the functions of the models, I came across this line.

Score(self, X, y[, sample_weight]) Returns the coefficient of determination R^2 of the prediction.

Does the score() method also return the coefficient of determination?

1

python pandas машинное-обучение numpy

Author: KordDEM, 2019-06-05

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1 answers

score 1 · Accepted Answer

I don't remember the method r2_score().

R2_score() is a regressor-independent metric function, and regression_class.score() - this is a class method that internally calls the metric r2_score()

Notes

The R2 score used when calling score on a regressor will use multioutput='uniform_average' from version 0.23 to keep consistent with metrics.r2_score. This will influence the score method of all the multioutput regressors (except for multioutput.MultiOutputRegressor). To specify the default value manually and avoid the warning, please either call metrics.r2_score directly or make a custom scorer with metrics.make_scorer (the built-in scorer 'r2' uses multioutput='uniform_average').