Options for controlling the genetic algorithm. See genAlgControl for details.
evaluator
The evaluator used to evaluate the fitness of a variable subset. See
evaluatorPLS, evaluatorLM or evaluatorUserFunction for details.
seed
Integer with the seed for the random number generator or NULL to automatically seed the RNG
Details
The GA generates an initial "population" of populationSize chromosomes where each initial
chromosome has a random number of randomly selected variables. The fitness of every chromosome is evaluated by
the specified evaluator. The default built-in PLS evaluator (see evaluatorPLS) is the preferred
evaluator.
Chromosomes with higher fitness have higher probability of mating with another chromosome. populationSize / 2 couples each create
2 children. The children are created by randomly mixing the parents' variables. These children make up the new generation and are again
selected for mating based on their fitness. A total of numGenerations generations are built this way.
The algorithm returns the last generation as well as the best elitism chromosomes from all generations.