936854579a3cc112f0686e397798d2aa73e5fab3,sklearn/metrics/_regression.py,,mean_squared_error,#,194

Before Change

                               weights=sample_weight)
    if isinstance(multioutput, str):
        if multioutput == "raw_values":
            return output_errors if squared else np.sqrt(output_errors)
        elif multioutput == "uniform_average":
            // pass None as weights to np.average: uniform mean
            multioutput = None

After Change

    output_errors = np.average((y_true - y_pred) ** 2, axis=0,
                               weights=sample_weight)

    if not squared:
        output_errors = np.sqrt(output_errors)

    if isinstance(multioutput, str):
        if multioutput == "raw_values":
            return output_errors
        elif multioutput == "uniform_average":

Instances