Regression
Mean bias error
Implemented
regression.mean_bias_errorDefinition
Average signed error: positive when the model over-predicts on average.
Formula
(1/n) Σ (ŷᵢ − yᵢ)
Range: (−∞, ∞) (0 = unbiased)
Inputs and outputs
- y_true: array of real targets
- y_pred: array of real predictions
- sample_weight: optional
Returns: MetricResult
Assumptions
No assumptions beyond valid, aligned inputs of the documented types.
Limitations
No metric-specific limitations are documented yet. Interpret the value alongside the task, data, and other metrics.
Python API
import evalsuite as es
es.mean_bias_error(yr, pr)References
- Willmott CJ, Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res. 2005;30:79-82.