Nothing
`cIndexKM` <-
function (y, x, index = "all")
{
kmeans_res <- y
#############################################
gss <- function(x, clsize, withins)
{
allmean <- colMeans(x)
dmean <- sweep(x, 2, allmean, "-")
allmeandist <- sum(dmean^2)
wgss <- sum(withins)
bgss <- allmeandist - wgss
list(wgss = wgss, bgss = bgss)
}
#############################################
### Function modified by SD and PL from the original "cIndexKM" in "cclust"
### to accommodate a single response variable as well as singleton groups
### and remove unwanted index.
### The index
################################################
calinski <- function(zgss, clsize)
{
n <- sum(clsize)
k <- length(clsize)
## undefined 0/0 for one class (or fewer in error cases)
if (k <= 1)
NA
else
zgss$bgss/(k - 1)/(zgss$wgss/(n - k))
}
################################################
ssi <- function(centers, clsize)
{
ncl <- dim(centers)[1]
nvar <- dim(centers)[2]
cmax <- apply(centers, 2, max)
cmin <- apply(centers, 2, min)
cord <- apply(centers, 2, order)
cmaxi <- cord[ncl, ]
cmini <- cord[1, ]
meanmean <- mean(centers)
absmdif <- abs(apply(centers, 2, mean) - meanmean)
span <- cmax - cmin
csizemax <- clsize[cmaxi]
csizemin <- clsize[cmini]
hiest <- nvar
hiestw <- hiest * max(max(csizemax), max(csizemin)) *
exp(-min(absmdif))
sist <- sum(span)/hiest
sistw <- (span * exp(-absmdif)) %*% sqrt(csizemax * csizemin)/hiestw
list(ssi = sist, ssiw = sistw)
}
################################################
zgss <- gss(x, kmeans_res$size, kmeans_res$withinss)
index <- pmatch(index, c("calinski", "ssi", "all"))
if (is.na(index))
stop("invalid clustering index")
if (index == -1)
stop("ambiguous index")
vecallindex <- numeric(3)
if (any(index == 1) || (index == 3))
vecallindex[1] <- calinski(zgss, kmeans_res$size)
if (any(index == 2) || (index == 3))
vecallindex[2] <- ssi(kmeans_res$centers, kmeans_res$size)$ssiw
names(vecallindex) <- c("calinski", "ssi")
if (index < 3)
vecallindex <- vecallindex[index]
vecallindex
}
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