gemseo.mlearning.regression.quality.me_measure module#

The maximum error to assess the quality of a regression algorithm.

The maximum error (ME) is defined by

$$operatorname{ME}(hat{y})=max_{1leq i leq n}|hat{y}_i-y_i|,$$

where $hat{y}$ are the predictions and $y$ are the data points.

class MEMeasure(algo, fit_transformers=False)[source]#

Bases: BaseRegressorQuality

The maximum error to assess the quality of a regressor.

Parameters:
  • algo (BaseRegressor) -- 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.