Nothing
AddCluster2Biplot <- function(Bip, NGroups=3, ClusterType="hi", Groups=NULL, Original=FALSE, ClusterColors=NULL, ...){
types = c("Hierarchical", "K-Means", "Gaussian Mixture", "User Privided")
ClusterTypes=c("hi", "km", "gm", "us")
if (is.numeric(ClusterType))
ClusterType = ClusterTypes[ClusterType]
Bip$ClusterType=ClusterType
clasebip=class(Bip)
if (ClusterType=="hi"){
if (NGroups<2) stop("You need at least 2 groups")
if (Original) {
if (clasebip=="ContinuousBiplot")
distances = dist(Bip$Scaled_Data)
if (clasebip=="External.Binary.Logistic.Biplot")
distances=as.dist(Bip$Proximities)}
else distances = dist(Bip$RowCoordinates)
hc=hclust(distances, ...)
Bip$Clusters = as.factor(cutree(hc,NGroups))
Bip$ClusterNames="Cluster 1"
for (k in 2:NGroups)
Bip$ClusterNames =c(Bip$ClusterNames, paste("Cluster",k))
hcd=as.dendrogram(hc)
Bip$ClusterObject=hc
}
if (ClusterType=="km"){
if (Original)
hc=kmeans(Bip$Scaled_Data, centers=NGroups, ...)
else
hc=kmeans(Bip$RowCoordinates, centers=NGroups, ...)
Bip$ClusterObject=hc
Bip$ClusterNames="Cluster 1"
for (k in 2:NGroups)
Bip$ClusterNames =c(Bip$ClusterNames, paste("Cluster",k))
Bip$Clusters = as.factor(hc$cluster)
}
if (ClusterType=="gm"){
if (Original)
hc=MGC(Bip$Scaled_Data, NG=NGroups, ...)
else
hc=MGC(Bip$RowCoordinates, NG=NGroups, ...)
Bip$Clusters = as.factor(hc$Classification)
Bip$P=hc$P
}
if (ClusterType=="us"){
if (!is.factor(Groups)) stop("Groups have to be defined as a factor")
NGroups=length(levels(Groups))
Bip$Clusters = Groups
Bip$ClusterNames = levels(Groups)
}
if (is.null(ClusterColors)){
palette(rainbow(NGroups))
ClusterColors = palette()
}
Bip$ClusterColors=ClusterColors
if (ClusterType=="hi"){
clusMember = cutree(hc, NGroups)
colLab <- function(n) {
if (is.leaf(n)) {
a <- attributes(n)
labCol <- ClusterColors[clusMember[which(names(clusMember) == a$label)]]
attr(n, "nodePar") <- c(a$nodePar, lab.col = labCol)
}
n
}
Bip$Dendrogram = dendrapply(hcd, colLab)
}
return(Bip)
}
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