sklearn.metrics.median_absolute_error¶
- sklearn.metrics.median_absolute_error(y_true, y_pred)[source]¶
Median absolute error regression loss
Parameters: 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.
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