Nothing
#Class implementing a Regression Algorithm
#Implements the GFS-GP-R KEEL regression algorithm
GFS_GP_R <- function(train, test, numLabels=3, numRules=8, popSize=30, numisland=2, steady=1, numIter=100, tourSize=4, mutProb=0.01, aplMut=0.1, probMigra=0.001, probOptimLocal=0.00, numOptimLocal=0, idOptimLocal=0, nichinggap=0, maxindniche=8, probintraniche=0.75, probcrossga=0.5, probmutaga=0.5, lenchaingap=10, maxtreeheight=8, seed=-1){
alg <- RKEEL::R6_GFS_GP_R$new()
alg$setParameters(train, test, numLabels, numRules, popSize, numisland, steady, numIter, tourSize, mutProb, aplMut, probMigra, probOptimLocal, numOptimLocal, idOptimLocal, nichinggap, maxindniche, probintraniche, probcrossga, probmutaga, lenchaingap, maxtreeheight, seed)
return (alg)
}
R6_GFS_GP_R <- R6::R6Class("R6_GFS_GP_R",
inherit = RegressionAlgorithm,
public = list(
#Public properties
#Number of labels
numLabels = 3,
#Number of rules
numRules = 8,
#Population size
popSize = 30,
#numisland
numisland = 2,
#steady
steady = 1,
#Number of iterations
numIter = 100,
#Tournament size
tourSize = 4,
#Mutation probabilitu
mutProb = 0.01,
#Amplmut
aplMut = 0.1,
#Prob migra
probMigra = 0.001,
#Prob local optim
probOptimLocal = 0.00,
#Number of optim local
numOptimLocal = 0,
#id optim local
idOptimLocal = 0,
#nichinggap
nichinggap = 0,
#maxindniche
maxindniche = 8,
#probintraniche
probintraniche = 0.75,
#probcrossga
probcrossga = 0.5,
#probmutaga
probmutaga = 0.5,
#lenchaingap
lenchaingap = 10,
#max tree height
maxtreeheight = 8,
#seed
seed = -1,
#Public functions
#Initialize function
setParameters = function(train, test, numLabels=3, numRules=8, popSize=30,
numisland=2, steady=1, numIter=100, tourSize=4,
mutProb=0.01, aplMut=0.1, probMigra=0.001,
probOptimLocal=0.00, numOptimLocal=0, idOptimLocal=0,
nichinggap=0, maxindniche=8, probintraniche=0.75,
probcrossga=0.5, probmutaga=0.5, lenchaingap=10,
maxtreeheight=8, seed=-1){
super$setParameters(train, test)
self$numLabels <- numLabels
self$numRules <- numRules
self$popSize <- popSize
self$numisland <- numisland
self$steady <- steady
self$numIter <- numIter
self$tourSize <- tourSize
self$mutProb <- mutProb
self$aplMut <- aplMut
self$probMigra <- probMigra
self$probOptimLocal <- probOptimLocal
self$numOptimLocal <- numOptimLocal
self$idOptimLocal <- idOptimLocal
self$nichinggap <- nichinggap
self$maxindniche <- maxindniche
self$probintraniche <- probintraniche
self$probcrossga <- probcrossga
self$probmutaga <- probmutaga
self$lenchaingap <- lenchaingap
self$maxtreeheight <- maxtreeheight
if(seed == -1) {
self$seed <- sample(1:1000000, 1)
}
else {
self$seed <- seed
}
}
),
private = list(
#Private properties
#jar Filename
jarName = "crispSymRegGAP.jar",
#algorithm name
algorithmName = "GFS-GP-R",
#String with algorithm name
algorithmString = "Fuzzy Rule Learning, Grammar-based GAP Algorithm",
#Private functions
#Get the text with the parameters for the config file
getParametersText = function(){
text <- ""
text <- paste0(text, "seed = ", self$seed, "\n")
text <- paste0(text, "subAlgorithm = ModelFuzzyGAP", "\n")
text <- paste0(text, "dataformat = keel", "\n")
text <- paste0(text, "numlabels = ", self$numLabels, "\n")
text <- paste0(text, "numrules = ", self$numRules, "\n")
text <- paste0(text, "outlabel = MFGAP", "\n")
text <- paste0(text, "popsize = ", self$popSize, "\n")
text <- paste0(text, "numisland = ", self$numisland, "\n")
text <- paste0(text, "steady = ", self$steady, "\n")
text <- paste0(text, "numitera = ", self$numIter, "\n")
text <- paste0(text, "toursize = ", self$tourSize, "\n")
text <- paste0(text, "probmuta = ", self$mutProb, "\n")
text <- paste0(text, "amplmuta = ", self$aplMut, "\n")
text <- paste0(text, "probmigra = ", self$probMigra, "\n")
text <- paste0(text, "proboptimlocal = ", self$probOptimLocal, "\n")
text <- paste0(text, "numoptimlocal = ", self$numOptimLocal, "\n")
text <- paste0(text, "idoptimlocal = ", self$idOptimLocal, "\n")
text <- paste0(text, "nichinggap = ", self$nichinggap, "\n")
text <- paste0(text, "maxindniche = ", self$maxindniche, "\n")
text <- paste0(text, "probintraniche = ", self$probintraniche, "\n")
text <- paste0(text, "probcrossga = ", self$probcrossga, "\n")
text <- paste0(text, "probmutaga = ", self$probmutaga, "\n")
text <- paste0(text, "lenchaingap = ", self$lenchaingap, "\n")
text <- paste0(text, "maxtreeheight = ", self$maxtreeheight, "\n")
return(text)
}
)
)
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