Genetic algorithm for feature engineering

This plugin provides recipes to create and select features with a genetic algorithm based on the DEAP framework

Genetic Algorithms are inspired by the concepts of evolution through natural selection. They are often used in high dimensional spaces where grid / random search would be prohibitive.

Genetic Algorithms encode the space to explore with genes and proceed by generations. For each generation:

  • individuals forming the current population are evaluated (fitness)
  • the best individuals are chosen to mix their genes together (crossover)
  • independent random changes are performed (mutation)

This plugins deals with feature creation and selection, powered by genetic algorithms. Starting from a dataset with features and a target, it will automatically select among features both from the dataset and their combinations (product, sum and differences). In this setting, an individual is represented by a boolean array with a value for every feature (originals and combinations) indicating whether it is selected or not as an input for the model to train.

Plugin Information

Version 0.0.2
Author Dataiku
Released 2018-08-01
Last updated 2018-08-01
License LGPL v3.0
Source code Github
Reporting issues Github

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