Modules

`lore_sa.bbox`: BlackBox abstract class

Generic Black Box class witch provides two sklearn-like methods.

`dataset.Dataset`	Generic class to handle datasets
`dataset.TabularDataset`	It provides an interface to handle datasets, including some essential information on the structure and semantic of the dataset.
`dataset.utils`

`neighgen.RandomGenerator`	Random Generator creates neighbor instances by generating random values starting from the instance to explain
`neighgen.GeneticGenerator`	Random Generator creates neighbor instances by generating random values starting from an input instance and pruning the generation around a fitness function based on proximity to the instance to explain

`discretizer.Discretizer`
`discretizer.RMEPDiscretizer`

`encoder_decoder.EncDec`	Generic class to implement an encoder/decoder
`encoder_decoder.OneHotEnc`	It provides an interface to access One Hot enconding (https://en.wikipedia.org/wiki/One-hot) functions.
`encoder_decoder.LabelEnc`	It provides an interface to access Label enconding functions.
`encoder_decoder.TabularEnc`	It combines different encoders/decoders over a table dataset

`explanation.Explanation`
`explanation.ExplanationEncoder`	Special json encoder for Rule types
`explanation.ImageExplanation`
`explanation.MultilabelExplanation`
`explanation.TextExplanation`
`explanation.json2explanation`

`rule.Rule`
`rule.RuleEncoder`	Special json encoder for Rule types
`rule.json2rule`
`rule.json2expression`
`rule.Expression`	Utility object to define a logical expression.

`surrogate.Surrogate`	Generic surrogate class
`surrogate.DecisionTreeSurrogate`