sklearn.metrics
.max_error¶
- sklearn.metrics.max_error(y_true, y_pred)[source]¶
The max_error metric calculates the maximum residual error.
Read more in the User Guide.
- Parameters
- y_truearray-like of shape (n_samples,)
Ground truth (correct) target values.
- y_predarray-like of shape (n_samples,)
Estimated target values.
- Returns
- max_errorfloat
A positive floating point value (the best value is 0.0).
Examples
>>> from sklearn.metrics import max_error >>> y_true = [3, 2, 7, 1] >>> y_pred = [4, 2, 7, 1] >>> max_error(y_true, y_pred) 1