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######################################################################################
# fugeR.predict
# TO DO: Change to make the prediction even if the dataset has not the same number of column.
#
#' Compute the prediction of a fuzzy system for the given input data.
#'
#' @param fuzzySystem [NULL] The fuzzy system to use for computing the prediction.
#' @param dataset [NULL] The data to use.
#'
#' @return \code{prediction}, A data.frame containing the predictions.
#'
#' @note The dataset must contain the same headers (in the same order) that the \code{data}
#' used to find the system with fugeR.run.
#'
#' @examples
#' ##
#' ##
#' \dontrun{
#' fis <- fugeR.run (
#' In,
#' Out,
#' generation=100,
#' population=200,
#' elitism=40,
#' verbose=TRUE,
#' threshold=0.5,
#' sensiW=1.0,
#' speciW=1.0,
#' accuW=0.0,
#' rmseW=1.0,
#' maxRules=10,
#' maxVarPerRule=2,
#' labelsMf=2
#' )
#'
#' prediction <- fugeR.predict( fis, In )
#' }
#'
#' @seealso \code{\link{fugeR.run}}
#'
#' @author Alexandre Bujard, HEIG-VD, Jul'2012
#'
#' @export
######################################################################################
fugeR.predict <- function( fuzzySystem=NULL,
dataset = NULL) {
#Fuzzify and apply AND (MIN) operator.
#Return a list for each rule of length equal to the number of case.
fuzzifiedValue <- fugeR.fuzzify(fuzzySystem, dataset)
#Defuzzify and make prediction.
#Return a lsit for each out of length equal to then number of case.
prediction <- fugeR.defuzzify(fuzzySystem, fuzzifiedValue)
return(data.frame(prediction))
}
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