Nothing
NEFRC = function(D, k, m, RS, startU,index,alpha,conv, maxit, seed = NULL)
{
if (missing(D))
stop("The distance matrix D must be given")
if (is.null(D))
stop("The distance matrix D is empty")
D=data.matrix(D)
n=nrow(D)
p=ncol(D)
distCheck(D,n,p)
if (is.null(rownames(D)))
rn=paste("Obj",1:n,sep=" ")
else
rn=rownames(D)
if (is.null(colnames(D)))
cn=paste("Var",1:p,sep=" ")
else
cn=colnames(D)
if (any(is.na(D)))
stop("The distance matrix D must not contain NA values")
if (!is.numeric(D))
stop("The distance matrix D is not a numeric data.frame or matrix")
if ((missing(startU)) || (is.null(startU)))
{
check=1
checkMiss = missing(k) || is.null(k) || !is.numeric(k)
if (checkMiss)
{
k= 2:6
cat("The default value k=2:6 has been set ",fill=TRUE)
}
nk <- length(k)
if(nk != 1){
if(!checkMiss){
checkK = any(k <= 1) | any((k-as.integer(k)) != 0)
if(checkK)
{
k = 2:6
nk <- length(k)
cat("The number of clusters k must be greter than 1, integer and numeric: the default value k=2:6 will be used ",fill=TRUE)
}else{
k <- sort(unique(k))
}
}
if (missing(index))
{
index = "SIL.F"
cat("The default index SIL.F has been set ",fill=TRUE)
}else{
if(length(index) != 1)
{
index = "SIL.F"
cat("The index must be a single value: SIL.F will be used ",fill=TRUE)
}else{
if(all(index!=c("PC","PE","MPC","SIL","SIL.F"))){
index = "SIL.F"
cat("No match found for the index name: SIL.F will be used ", fill = TRUE)
}
}
}
if(index == "SIL.F"){
if (missing(alpha))
{
alpha=1
cat("The default value alpha=1 has been set for computing SIL.F ",fill=TRUE)
}else{
if (!is.numeric(alpha))
{
alpha=1
cat("The weighting coefficient alpha is not numeric: the default value alpha=1 will be used for computing SIL.F ",fill=TRUE)
}
if (alpha<0)
{
alpha=1
cat("The number of clusters k must be non negative: the value alpha=1 will be used for computing SIL.F ",fill=TRUE)
}
}
}else{
alpha = 1
}
}else{
nk <- 1
if (missing(index))
{
index = "SIL.F"
}else{
if(length(index) != 1)
{
index = "SIL.F"
cat("The index must be a single value: SIL.F will be used ",fill=TRUE)
}else{
if(!any(index==c("PC","PE","MPC","SIL","SIL.F"))){
index = "SIL.F"
cat("No match found for the index name: SIL.F will be used ", fill = TRUE)
}
}
}
if(index == "SIL.F"){
if (missing(alpha))
{
alpha=1
}else{
if (!is.numeric(alpha))
{
alpha=1
cat("The weighting coefficient alpha is not numeric: the default value alpha=1 will be used for computing SIL.F ",fill=TRUE)
}
if (alpha<0)
{
alpha=1
cat("The number of clusters k must be non negative: the value alpha=1 will be used for computing SIL.F ",fill=TRUE)
}
}
}else{
alpha = 1
}
if (!is.numeric(k))
{
k=2
cat("The number of clusters k is not numeric: the default value k=2 will be used ",fill=TRUE)
}
if ((k>ceiling(n/2)) || (k<2))
{
k=2
cat("The number of clusters k must be an integer in {2, 3, ..., ceiling(n/2)}: the default value k=2 will be used ",fill=TRUE)
}
if (k%%ceiling(k)>0)
{
k=ceiling(k)
cat("The number of clusters k must be an integer in {2, 3, ..., ceiling(nrow(X)/2)}: the value ceiling(k) will be used ",fill=TRUE)
}
}
}else
{
startU=as.matrix(startU)
ns=nrow(startU)
k=ncol(startU)
check=0
nk = 1
if (any(is.na(startU)))
{
k=2
cat("The rational start must not contain NA values: the default value k=2 and a random start will be used ",fill=TRUE)
check=1
}
if (!is.numeric(startU))
{
k=2
cat("The rational start is not a numeric data.frame or matrix: the default value k=2 and a random start will be used ",fill=TRUE)
check=1
}
if ((k>ceiling(n/2)) || (k<2))
{
k=2
cat("The number of clusters k must be an integer in {2, 3, ..., ceiling(n/2)}: the default value k=2 and a random start will be used ",fill=TRUE)
check=1
}
if ((ns!=n) && (check=0))
{
cat("The number of rows of startU is different from that of X: k=ncol(startU) and a random start will be used ",fill=TRUE)
check=1
}
if (any(apply(startU,1,sum)!=1))
{
startU=startU/apply(startU,1,sum)
cat("The sums of the rows of startU must be equal to 1: the rows of startU will be normalized to unit row-wise sum ",fill=TRUE)
}
if (missing(index))
{
index = "SIL.F"
}else{
if(length(index) != 1)
{
index = "SIL.F"
cat("The index must be a single value: SIL.F will be used ",fill=TRUE)
}else{
if(!any(index==c("PC","PE","MPC","SIL","SIL.F","XB"))){
index = "SIL.F"
cat("No match found for the index name: SIL.F will be used ", fill = TRUE)
}
}
}
if(index == "SIL.F"){
if (missing(alpha))
{
alpha=1
}else{
if (!is.numeric(alpha))
{
alpha=1
cat("The weighting coefficient alpha is not numeric: the default value alpha=1 will be used for computing SIL.F ",fill=TRUE)
}
if (alpha<0)
{
alpha=1
cat("The number of clusters k must be non negative: the value alpha=1 will be used for computing SIL.F ",fill=TRUE)
}
}
}else{
alpha = 1
}
}
if (missing(m))
{
m=2
}
if (!is.numeric(m))
{
m=2
cat("The parameter of fuzziness m is not numeric: the default value m=2 will be used ",fill=TRUE)
}
if (m<=1)
{
m=2
cat("The parameter of fuzziness m must be >1: the default value m=2 will be used ",fill=TRUE)
}
if (missing(RS))
{
RS=1
}
if (!is.numeric(RS))
{
cat("The number of starts RS is not numeric: the default value RS=1 will be used ",fill=TRUE)
RS=1
}
if (RS<1)
{
cat("The number of starts RS must be an integer >=1: the default value RS=1 will be used ",fill=TRUE)
RS=1
}
if (RS%%ceiling(RS)>0)
{
cat("The number of starts RS must be an integer >=1: the value ceiling(RS) will be used ",fill=TRUE)
RS=ceiling(RS)
}
if (missing(conv))
conv=1e-9
if (conv<=0)
{
cat("The convergence criterion conv must be a (small) value >0: the default value conv=1e-9 will be used ",fill=TRUE)
conv=1e-9
}
if (!is.numeric(conv))
{
cat("The convergence criterion conv is not numeric: the default value conv=1e-9 will be used ",fill=TRUE)
conv=1e-9
}
if (missing(maxit))
maxit=1e+6
if (!is.numeric(maxit))
{
cat("The maximum number of iterations maxit is not numeric: the default value maxit=1e+6 will be used ",fill=TRUE)
maxit=1e+6
}
if (maxit<=0)
{
cat("The maximum number of iterations maxit must be an integer >0: the default value maxit=1e+6 will be used ",fill=TRUE)
maxit=1e+6
}
if (maxit%%ceiling(maxit)>0)
{
cat("The maximum number of iterations maxit must be an integer >0: the value ceiling(maxit) will be used ",fill=TRUE)
maxit=ceiling(maxit)
}
if(!is.null(seed))
{
if (!is.numeric(seed))
{
cat("The seed value is not numeric: set.seed(NULL) will be used ",fill=TRUE)
set.seed(NULL)
}else{
set.seed(seed)
}
}
crit.f <- rep(NA,nk)
crit = 0
for(c in 1:nk)
{
if ((check!=1))
{
main.temp <- mainnefrc_U(D = D,U = startU,m = m,n = n,k = k[c],index = index,alpha = alpha,conv = conv,maxit = maxit)
}else{
main.temp <- mainnefrc(D = D,m = m,n = n,k = k[c],index = index,alpha = alpha,rs = RS,maxit = maxit,conv = conv)
}
crit.temp = main.temp$index_max
crit.f[c] = main.temp$index
if(c == 1 | crit < crit.temp)
{
main = main.temp
crit = crit.temp
}
}
value = as.vector(main$value)
it = as.vector(main$iter)
U.opt = main$U
names(crit.f) = paste(index," ","k=",k,sep="")
k = main$k
rownames(U.opt)=rn
colnames(U.opt)=paste("Clus",1:k,sep=" ")
names(value)=paste("Start",1:RS,sep=" ")
names(it)=names(value)
names(k)=c("Number of clusters")
names(m)=c("Parameter of fuzziness")
clus = cl.memb(U.opt)
out = list(U=U.opt,
H=NULL,
F=NULL,
clus=clus,
medoid=NULL,
value=value,
criterion = crit.f,
iter=it,
k=k,
m=m,
ent=NULL,
b=NULL,
vp=NULL,
delta=NULL,
stand=NULL,
D = D,
call=match.call())
class(out)=c("fclust")
return(out)
}
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