criterion module¶
Common expected improvement of the regression model.
This is the same as the expected improvement of the regression model for the minimum.
Statistics:
where \(y_{min}=\min_{1\leq i \leq n}~y^{(i)}\).
Bootstrap estimator:
- class gemseo_mlearning.adaptive.criteria.optimum.criterion.ExpectedImprovement(algo_distribution, **options)[source]
Bases:
MinExpectedImprovement
The expected improvement.
This criterion is scaled by the output range.
# noqa: D205 D212 D415
- Parameters:
algo_distribution (MLRegressorDistribution) – The distribution of a machine learning algorithm.
**options (MLDataAcquisitionCriterionOptionType) – The acquisition criterion options.
- algo_distribution: MLRegressorDistribution
The distribution of a machine learning algorithm assessor.
- force_real: bool
Whether to cast the results to real value.
- has_default_name: bool
Whether the name has been set with a default value.
- last_eval: OutputType | None
The value of the function output at the last evaluation.
None
if it has not yet been evaluated.
- output_range: float
The output range.
- special_repr: str
The string representation of the function overloading its default string ones.