sklearn.metrics.median_absolute_error¶
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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
