GenAlgControl-class: Control class for the genetic algorithm

In gaselect: Genetic Algorithm (GA) for Variable Selection from High-Dimensional Data

Control class for the genetic algorithm

Description

This class controls the general setup of the genetic algorithm

Slots

populationSize

The number of "chromosomes" in the population (between 1 and 2^16).

numGenerations

The number of generations to produce (between 1 and 2^16).

minVariables

The minimum number of variables in the variable subset (between 0 and p - 1 where p is the total number of variables).

maxVariables

The maximum number of variables in the variable subset (between 1 and p, and greater than minVariables).

elitism

The number of absolute best chromosomes to keep across all generations (between 1 and min(populationSize * numGenerations, 2^16)).

mutationProbability

The probability of mutation (between 0 and 1).

badSolutionThreshold

The child must not be more than badSolutionThreshold percent worse than the worse parent. If less than 0, the child must be even better than the worst parent.

crossover

The crossover method to use

crossoverId

The numeric ID of the crossover method to use

maxDuplicateEliminationTries

The maximum number of tries to eliminate duplicates

verbosity

The level of verbosity. 0 means no output at all, 2 is very verbose.

gaselect documentation built on April 15, 2025, 1:29 a.m.