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Optimize by Generation (Evolutionary Aggregation)

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​

This is an example set input port

Output​

example set​

This is an example set output port

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