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##################################################################################
# MixmodDAResults.R ##
##################################################################################
#' @include global.R
#' @include MixmodResults.R
NULL
#' Constructor of [\code{\linkS4class{MixmodDAResults}}] class
#'
#' This is a class to contain results after a discriminant analysis with MIXMOD.
#' Inherits the [\code{\linkS4class{MixmodResults}}] class.
#'
#' \describe{
#' \item{CVLabel}{vector of integers containing labels defined by cross validation.}
#' \item{CVClassification}{classification table after cross validation.}
#' \item{MAPErrorRate}{error rate done by MAP algorithm.}
#' \item{MAPClassification}{classification table after MAP algorithm.}
#' }
#'
#' @examples
#' getSlots("MixmodDAResults")
#' @name MixmodDAResults-class
#' @rdname MixmodDAResults-class
#' @exportClass MixmodDAResults
#'
setClass(
Class = "MixmodDAResults",
representation = representation(
CVLabel = "integer",
CVClassification = "matrix",
MAPErrorRate = "numeric",
MAPClassification = "matrix"
),
contains = c("MixmodResults"),
prototype = prototype(
CVLabel = integer(0),
MAPErrorRate = numeric(0),
CVClassification = matrix(nrow = 0, ncol = 0),
MAPClassification = matrix(nrow = 0, ncol = 0)
)
)
#' @rdname print-methods
#' @aliases print print,MixmodDAResults-method
#'
setMethod(
f = "print",
signature = c("MixmodDAResults"),
function(x, ...) {
callNextMethod()
if (length(x@CVLabel) > 0) {
cat("* Classification with CV:\n")
cat(" |")
line <- c("-----------")
for (i in 1:x@nbCluster) {
cat(" Cluster", i, "|")
line <- c(line, "-----------")
}
cat("\n")
cat(line, "\n")
for (i in 1:x@nbCluster) {
cat(" Cluster", i, "|")
for (j in 1:x@nbCluster) {
cat(formatC(x@CVClassification[i, j], digits = 9, format = "d"), "|")
}
cat("\n")
}
cat(line, "\n")
cat("* Error rate with CV = ", formatC((1 - x@criterionValue) * 100, digits = 2, format = "f"), "%\n\n")
}
cat("* Classification with MAP:\n")
cat(" |")
line <- c("-----------")
for (i in 1:x@nbCluster) {
cat(" Cluster", i, "|")
line <- c(line, "-----------")
}
cat("\n")
cat(line, "\n")
for (i in 1:x@nbCluster) {
cat(" Cluster", i, "|")
for (j in 1:x@nbCluster) {
cat(formatC(x@MAPClassification[i, j], digits = 9, format = "d"), "|")
}
cat("\n")
}
cat(line, "\n")
cat("* Error rate with MAP = ", formatC(x@MAPErrorRate * 100, digits = 2, format = "f"), "%\n")
cat("****************************************\n")
}
)
#' @rdname show-methods
#' @aliases show show,MixmodDAResults-method
#'
setMethod(
f = "show",
signature = c("MixmodDAResults"),
function(object) {
callNextMethod()
if (length(object@CVLabel) > 0) {
cat("* Classification with CV:\n")
cat(" |")
line <- c("-----------")
for (i in 1:object@nbCluster) {
cat(" Cluster", i, "|")
line <- c(line, "-----------")
}
cat("\n")
cat(line, "\n")
for (i in 1:object@nbCluster) {
cat(" Cluster", i, "|")
for (j in 1:object@nbCluster) {
cat(formatC(object@CVClassification[i, j], digits = 9, format = "d"), "|")
}
cat("\n")
}
cat(line, "\n")
cat("* Error rate with CV = ", formatC((1 - object@criterionValue) * 100, digits = 2, format = "f"), "%\n\n")
}
cat("* Classification with MAP:\n")
cat(" |")
line <- c("-----------")
for (i in 1:object@nbCluster) {
cat(" Cluster", i, "|")
line <- c(line, "-----------")
}
cat("\n")
cat(line, "\n")
for (i in 1:object@nbCluster) {
cat(" Cluster", i, "|")
for (j in 1:object@nbCluster) {
cat(formatC(object@MAPClassification[i, j], digits = 9, format = "d"), "|")
}
cat("\n")
}
cat(line, "\n")
cat("* Error rate with MAP = ", formatC(object@MAPErrorRate * 100, digits = 2, format = "f"), "%\n")
cat("****************************************\n")
}
)
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