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#Class implementing a Classification Algorithm
#Implements the GFS-AdaBoost-C KEEL classification algorithm
GFS_AdaBoost_C <- function(train, test, numLabels=3, numRules=8, seed=-1){
alg <- RKEEL::R6_GFS_AdaBoost_C$new()
alg$setParameters(train, test, numLabels, numRules, seed)
return (alg)
}
R6_GFS_AdaBoost_C <- R6::R6Class("R6_GFS_AdaBoost_C",
inherit = ClassificationAlgorithm,
public = list(
#Public properties
#Number of labels
numLabels = 3,
#Number of rules
numRules = 8,
#seed
seed = -1,
#Public functions
#Initialize function
setParameters = function(train, test, numLabels=3, numRules=8, seed=-1){
super$setParameters(train, test)
self$numLabels <- numLabels
self$numRules <- numRules
if(seed == -1) {
self$seed <- sample(1:1000000, 1)
}
else {
self$seed <- seed
}
}
),
private = list(
#Private properties
#jar Filename
jarName = "ClassifierFuzzyAdaBoost.jar",
#algorithm name
algorithmName = "GFS-AdaBoost-C",
#String with algorithm name
algorithmString = "Fuzzy Rule Learning, AdaBoost Algorithm",
#Private functions
#Get the text with the parameters for the config file
getParametersText = function(){
text <- ""
text <- paste0(text, "seed = ", self$seed, "\n")
text <- paste0(text, "subAlgorithm = ClasifFuzzyAdaBoost", "\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 = FAB", "\n")
return(text)
}
)
)
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