Synopsis
A generating genetic algorithm for unsupervised learning (experimental).
Description
Performs an evolutionary feature aggregation. Each base feature is only allowed to be used as base feature, in one merged feature, or it may not be used at all.
Input
- example set in: expects: ExampleSet
Output
- example set out:
- performance vector out:
Parameters
- aggregation function: The aggregation function which is used for feature aggregations.
- population size: Number of individuals per generation.
- maximum number of generations: Number of generations after which to terminate the algorithm.
- selection type: The type of selection.
- tournament fraction: The fraction of the population which will participate in each tournament.
- crossover type: The type of crossover.
- p crossover: Probability for an individual to be selected for crossover.
- population criteria data file: The path to the file in which the criteria data of the final population should be saved.
- use local random seed: Indicates if a local random seed should be used.
- local random seed: Specifies the local random seed