UniformStrategy

class aixd.sampler.strategies.UniformStrategy(features: DataObject | List[DataObject], engine: SamplingEngine | str = 'random', **kwargs)

Bases: Strategy

Scales and shifts the samples from [0, 1] to [feature.min, feature.max]) for continuous features, or discretises them through binning.

Parameters:

• features (Union[DataObject, List[DataObject]]) – The features refer to the data objects, which contain the information about the domain of the features.

• engine (Union[SamplingEngine, str], optional, default=”random”) – In this case the default engine is “random”, as it is the only one that makes sense to use with this strategy.

Methods

sample

Inherited Methods

fit	Fit the strategy to the data, also using some vectors of objectives and validity values.
reset_states	Reset the state of the engine.
update	Updates the state of the sampling methods by providing the performance of the generated samples in the form of objectives and validity.