Description Usage Arguments Value See Also
Perform symbolic regression via untyped multiniche genetic programming.
The regression task is specified as a formula
. Only simple
formulas without interactions are supported. The result of the symbolic
regression run is a symbolic regression model containing an untyped GP
population of model functions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  multiNicheSymbolicRegression(formula, data,
stopCondition = makeTimeStopCondition(25),
passStopCondition = makeTimeStopCondition(5), numberOfNiches = 2,
clusterFunction = groupListConsecutive, joinFunction = function(niches)
Reduce(c, niches), population = NULL, populationSize = 100,
eliteSize = ceiling(0.1 * populationSize), elite = list(),
individualSizeLimit = 64, penalizeGenotypeConstantIndividuals = FALSE,
functionSet = mathFunctionSet, constantSet = numericConstantSet,
selectionFunction = makeTournamentSelection(),
crossoverFunction = crossover, mutationFunction = NULL,
restartCondition = makeEmptyRestartCondition(),
restartStrategy = makeLocalRestartStrategy(), progressMonitor = NULL,
verbose = TRUE, clusterApply = sfClusterApplyLB,
clusterExport = sfExport)

formula 
A 
data 
A 
stopCondition 
The stop condition for the evolution main loop. See

passStopCondition 
The stop condition for each parallel pass. See

numberOfNiches 
The number of niches to cluster the population into. 
clusterFunction 
The function used to cluster the population into
niches. The first parameter of this function is a GP population, the
second paramater an integer representing the number of niches. Defaults
to 
joinFunction 
The function used to join all niches into a population again after a round of parallel passes. Defaults to a function that simply concatenates all niches. 
population 
The GP population to start the run with. If this parameter
is missing, a new GP population of size 
populationSize 
The number of individuals if a population is to be created. 
eliteSize 
The number of "elite" individuals to keep. Defaults to

elite 
The elite list, must be alist of individuals sorted in ascending order by their first fitness component. 
individualSizeLimit 
Individuals with a number of tree nodes that
exceeds this size limit will get a fitness of 
penalizeGenotypeConstantIndividuals 
Individuals that do not contain
any input variables will get a fitness of 
functionSet 
The function set. 
constantSet 
The set of constant factory functions. 
selectionFunction 
The selection function to use. Defaults to tournament selection. See makeTournamentSelection for details. 
crossoverFunction 
The crossover function. 
mutationFunction 
The mutation function. 
restartCondition 
The restart condition for the evolution main loop. See makeFitnessStagnationRestartCondition for details. 
restartStrategy 
The strategy for doing restarts. See makeLocalRestartStrategy for details. 
progressMonitor 
A function of signature

verbose 
Whether to print progress messages. 
clusterApply 
The cluster apply function that is used to distribute the parallel passes to CPUs in a compute cluster. 
clusterExport 
A function that is used to export R variables to the nodes of
a CPU cluster, defaults to snowfall's 
An symbolic regression model that contains an untyped GP population.
predict.symbolicRegressionModel
, geneticProgramming
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