Optimize by Generation (GGA)


Synopsis

A genetic algorithm for feature selection and feature generation (GGA).


Description

In contrast to the class GeneticAlgorithm, the GeneratingGeneticAlgorithm generates new attributes and thus can change the length of an individual. Therfore specialized mutation and crossover operators are being applied. Generators are chosen at random from a list of generators specified by boolean parameters. Since this operator does not contain algorithms to extract features from value series, it is restricted to example sets with only single attributes. For automatic feature extraction from values series the value series plugin for RapidMiner written by Ingo Mierswa should be used. It is available at <a href="http://rapid-i.com">http://rapid-i.com</a>


Input


Output


Parameters


ExampleProcess