Description Usage Arguments Value See Also
View source: R/data_driven_gp.r
Perform an untyped genetic programming using a fitness function that depends
on a R data frame. Typical applications are data mining tasks such as symbolic
regression or classification. The task is specified as a formula
and a fitness function factory. Only simple formulas without interactions are
supported. The result of the datadriven GP run is a model structure containing
the formulas and an untyped GP population.
This function is primarily an intermediate for extensions. Endusers will
probably use more specialized GP tools such as symbolicRegression
.
1 2 3 4 5 6 7 8 9 10 11 12  dataDrivenGeneticProgramming(formula, data, fitnessFunctionFactory,
fitnessFunctionFactoryParameters = list(),
stopCondition = makeTimeStopCondition(5), population = NULL,
populationSize = 100, eliteSize = ceiling(0.1 * populationSize),
elite = list(), extinctionPrevention = FALSE, archive = FALSE,
functionSet = mathFunctionSet, constantSet = numericConstantSet,
crossoverFunction = NULL, mutationFunction = NULL,
restartCondition = makeEmptyRestartCondition(),
restartStrategy = makeLocalRestartStrategy(),
searchHeuristic = makeAgeFitnessComplexityParetoGpSearchHeuristic(),
breedingFitness = function(individual) TRUE, breedingTries = 50,
progressMonitor = NULL, verbose = TRUE)

formula 
A 
data 
A 
fitnessFunctionFactory 
A function that accepts two parameters, a
codeformula, data (given as a model frame) and the additional parameters
given in 
fitnessFunctionFactoryParameters 
Additional parameters to pass to the

stopCondition 
The stop condition for the evolution main loop. See

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. 
extinctionPrevention 
When set to 
archive 
If set to 
functionSet 
The function set. 
constantSet 
The set of constant factory functions. 
crossoverFunction 
The crossover function. 
mutationFunction 
The mutation function. 
restartCondition 
The restart condition for the evolution main loop. See makeEmptyRestartCondition for details. 
restartStrategy 
The strategy for doing restarts. See makeLocalRestartStrategy for details. 
searchHeuristic 
The searchheuristic (i.e. optimization algorithm) to use
in the search of solutions. See the documentation for 
breedingFitness 
A "breeding" function. This function is applied after
every stochastic operation Op that creates or modifies an individal
(typically, Op is a initialization, mutation, or crossover operation). If
the breeding function returns 
breedingTries 
In case of a boolean 
progressMonitor 
A function of signature

verbose 
Whether to print progress messages. 
A model structure that contains the formula and an untyped GP population.
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