mlproject.training.feature_selection

mlproject.training.feature_selection#

Functions for feature reduction and selection.

Functions

`cxTwoPointAndFix`	Crossover two individuals and fix them to have a specific number of selected features.
`get_relevant_features`	Build and apply a feature selection pipeline to remove correlated and irrelevant features.
`hamming_distance`	Calculate the Hamming distance between two individuals.
`init_valid_individual`	Initialize an individual with a fixed number of selected features.
`is_diverse`	Check if an individual is diverse enough from a population based on Hamming distance.
`mixed_selection`	Mixed selection strategy: combines elitism and random selection.
`mutate_and_fix`	Mutate an individual and ensure it has exactly num_selected_features selected.
`population_entropy`	Calculate the entropy of a population of binary individuals.

Classes

Genetic Algorithm Feature Selector using DEAP.