(AI Studio Core)
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 (IOObject)This is an example set input port
Output
- example set (Data table)
This is an example set output port
performance vector out (Performance Vector)
Parameters
- aggregation functionThe aggregation function which is used for feature aggregations.
- population sizeNumber of individuals per generation.
- maximum number of generationsNumber of generations after which to terminate the algorithm.
- selection typeThe type of selection.
- tournament fractionThe fraction of the population which will participate in each tournament.
- crossover typeThe type of crossover.
- p crossoverProbability for an individual to be selected for crossover.
- population criteria data fileThe path to the file in which the criteria data of the final population should be saved.
- use local random seedIndicates if a local random seed should be used.
- local random seedSpecifies the local random seed