sklearn.metrics.median_absolute_error

sklearn.metrics.median_absolute_error(y_true, y_pred) [source]

Median absolute error regression loss

Read more in the User Guide.

Parameters:	y_true : array-like of shape = (n_samples) Ground truth (correct) target values. y_pred : array-like of shape = (n_samples) Estimated target values.
Returns:	loss : float A positive floating point value (the best value is 0.0).

Examples

>>> from sklearn.metrics import median_absolute_error
>>> y_true = [3, -0.5, 2, 7]
>>> y_pred = [2.5, 0.0, 2, 8]
>>> median_absolute_error(y_true, y_pred)
0.5