sklearn.metrics.explained_variance_score()

y_true : array-like of shape = (n_samples) or (n_samples, n_outputs)

Ground truth (correct) target values.

y_pred : array-like of shape = (n_samples) or (n_samples, n_outputs)

Estimated target values.

sample_weight : array-like of shape = (n_samples), optional

Sample weights.

multioutput : string in [?raw_values?, ?uniform_average?, ?variance_weighted?] or array-like of shape (n_outputs)

Defines aggregating of multiple output scores. Array-like value defines weights used to average scores.

?raw_values? :

Returns a full set of scores in case of multioutput input.

?uniform_average? :

Scores of all outputs are averaged with uniform weight.

?variance_weighted? :

Scores of all outputs are averaged, weighted by the variances of each individual output.