mae_measure module¶
The mean absolute error to measure the quality of a regression algorithm.
The mean absolute error (MAE) is defined by
\[\operatorname{MAE}(\hat{y})=\frac{1}{n}\sum_{i=1}^n\|\hat{y}_i-y_i\|,\]
where \(\hat{y}\) are the predictions and \(y\) are the data points.
- class gemseo_mlearning.quality_measures.mae_measure.MAEMeasure(algo, fit_transformers=False)[source]
Bases:
MLErrorMeasure
The mean absolute error measure for machine learning.
- Parameters:
algo (MLRegressionAlgo) – A machine learning algorithm for supervised learning.
fit_transformers (bool) –
Whether to re-fit the transformers when using resampling techniques. If
False
, use the transformers of the algorithm fitted from the whole learning dataset.By default it is set to False.
- algo: MLSupervisedAlgo
The machine learning algorithm whose quality we want to measure.