Modules

`lore_sa.bbox`: BlackBox abstract class

Abstract base class for wrapping black box models.

`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`	Abstract base class for encoding and decoding features.
`encoder_decoder.ColumnTransformerEnc`	It provides an interface to access One Hot enconding (https://en.wikipedia.org/wiki/One-hot) functions.

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

`rule.Rule`	Decision rule with premises (conditions) and consequences (predictions).
`rule.RuleEncoder`	Special json encoder for Rule types
`rule.json2rule`
`rule.json2expression`
`rule.Expression`	Logical expression representing a condition in a rule.

`surrogate.Surrogate`	Abstract base class for interpretable surrogate models.
`surrogate.DecisionTreeSurrogate`