cgp: cgp

In porteous54/caRtesian: An implementation of Cartesian Genetic Programming in R

Description

Performs Cartesian Genetic Programming using the parameters provided.

Usage

cgp(dataset, model, functionSet = mathOpSet(), maxGenerations,
  fitnessFunction = mae, selectionMethod = list(func = muLambdaStrategy,
  args = c(population = NA, 4, NA)), rowsFuncNodes, colsFuncNodes, levelsBack,
  popSize = 5, updateFreq = 10)

Arguments

dataset	the dataset to use for training
model	a model specifying the output and input fields of the dataset
functionSet	the functions that can be used in the function nodes
maxGenerations	the maximum generations of the evolutionary process
fitnessFunction	the fitness function to use
selectionMethod	the function and parameters to use for selection
rowsFuncNodes	the number of rows to use in the function node structure
colsFuncNodes	the number of columns to use in the function node structure
levelsBack	the number of columns back that a function node can access
popSize	the number of solutions to generate in each generation
updateFreq	how many generations pass between updates on progress

Value

a list containing the best solution found and the chosen functionSet

porteous54/caRtesian documentation built on May 30, 2019, 11:43 a.m.