bigframes.ml.metrics.mean_squared_error#

bigframes.ml.metrics.mean_squared_error(y_true:DataFrame|Series,y_pred:DataFrame|Series)→float[source]#

Mean squared error regression loss.

Examples:

>>>importbigframes.pandasasbpd>>>importbigframes.ml.metrics

>>>y_true=bpd.DataFrame([3,-0.5,2,7])>>>y_pred=bpd.DataFrame([2.5,0.0,2,8])>>>mse=bigframes.ml.metrics.mean_squared_error(y_true,y_pred)>>>msenp.float64(0.375)

Parameters:

• y_true (Series orDataFrame ofshape (n_samples,)) – Ground truth (correct) target values.

• y_pred (Series orDataFrame ofshape (n_samples,)) – Estimated target values.

Returns:

Mean squared error.

Return type:

float