breed: breed

In jtkwar/GA: Genetic Algorithm for Variable Selection in Regression Problems

Description

This function returns P candidates of the next generation based on the pairs of parents. Crossover and mutation is also contained within this function.

Usage

breed(candidate, c, P, parent.pairs, mu, crossover_points, fitness_values, Gap)

Arguments

candidate	Each row of this matrix corresponds to a candidate model of current generation.
c	The number of chromosomes for each candidate function.
parent.pairs	Matrix of parent breeding pairs, a result of the select_parents function.
mu	(float) This is the mutation rate of chromosomes in each candidate function
crossover_points	Number of crossover points to be used in the bredding step.
fitness_values	These are calculated fitness values of the present generation. This comes in the form of a vector, and fitness values at a particular index corresponds to the candidate function of the same index in the candidate function
Gap	Generation gap for replacement of parents with offspring from each created iteration of the GA
offspring	(data frame) contains the offspring produced from crossover
mu	Mutation rate of the each allele within an offspring

Value

generation(binary matrix P x c): P candidates

offspring (data frame) Offspring data frame after mutation

jtkwar/GA documentation built on May 28, 2019, 7:36 a.m.