Hi.
I am trying to modify kmeans function.
It seems that is failing something obvious with the workspace.
I am a newbie and here is my code:
myk = function (x, centers, iter.max = 10, nstart = 1, algorithm =
c("Hartigan-Wong",
+ "Lloyd", "Forgy", "MacQueen"))
+ {
+ do_one <- function(nmeth) {
+ Z <- switch(nmeth, {
+ Z <- .Fortran(R_kmns, as.double(x), as.integer(m),
+ as.integer(ncol(x)), centers = as.double(centers),
+ as.integer(k), c1 = integer(m), integer(m), nc = integer(k),
+ double(k), double(k), integer(k), double(m),
+ integer(k), integer(k), as.integer(iter.max),
+ wss = double(k), ifault = 0L)
+ switch(Z$ifault, stop("empty cluster: try a better set
of initial centers",
+ call. = FALSE), warning(gettextf("did not converge
in %d iterations",
+ iter.max), call. = FALSE, domain = NA), stop("number
of cluster centres must lie between 1 and nrow(x)",
+ call. = FALSE))
+ Z
+ }, {
+ Z <- .C(R_kmeans_Lloyd, as.double(x), as.integer(m),
+ as.integer(ncol(x)), centers = as.double(centers),
+ as.integer(k), c1 = integer(m), iter = as.integer(iter.max),
+ nc = integer(k), wss = double(k))
+ myIter=Z$iter
+ if (Z$iter > iter.max) warning("did not converge in ",
+ iter.max, " iterations", call. = FALSE)
+ if (any(Z$nc == 0)) warning("empty cluster: try a better
set of initial centers",
+ call. = FALSE)
+ Z
+
+ }, {
+ Z <- .C(R_kmeans_MacQueen, as.double(x), as.integer(m),
+ as.integer(ncol(x)), centers = as.double(centers),
+ as.integer(k), c1 = integer(m), iter = as.integer(iter.max),
+ nc = integer(k), wss = double(k))
+ if (Z$iter > iter.max) warning("did not converge in ",
+ iter.max, " iterations", call. = FALSE)
+ if (any(Z$nc == 0)) warning("empty cluster: try a better
set of initial centers",
+ call. = FALSE)
+ Z
+ })
+ Z
+ }
+ x <- as.matrix(x)
+ m <- nrow(x)
+ if (missing(centers))
+ stop("'centers' must be a number or a matrix")
+ nmeth <- switch(match.arg(algorithm), `Hartigan-Wong` = 1,
+ Lloyd = 2, Forgy = 2, MacQueen = 3)
+ if (length(centers) == 1L) {
+ if (centers == 1)
+ nmeth <- 3
+ k <- centers
+ if (nstart == 1)
+ centers <- x[sample.int(m, k), , drop = FALSE]
+ if (nstart >= 2 || any(duplicated(centers))) {
+ cn <- unique(x)
+ mm <- nrow(cn)
+ if (mm < k)
+ stop("more cluster centers than distinct data points.")
+ centers <- cn[sample.int(mm, k), , drop = FALSE]
+ }
+ }
+ else {
+ centers <- as.matrix(centers)
+ if (any(duplicated(centers)))
+ stop("initial centers are not distinct")
+ cn <- NULL
+ k <- nrow(centers)
+ if (m < k)
+ stop("more cluster centers than data points")
+ }
+ if (iter.max < 1)
+ stop("'iter.max' must be positive")
+ if (ncol(x) != ncol(centers))
+ stop("must have same number of columns in 'x' and 'centers'")
+ Z <- do_one(nmeth)
+ best <- sum(Z$wss)
+ if (nstart >= 2 && !is.null(cn))
+ for (i in 2:nstart) {
+ centers <- cn[sample.int(mm, k), , drop = FALSE]
+ ZZ <- do_one(nmeth)
+ if ((z <- sum(ZZ$wss)) < best) {
+ Z <- ZZ
+ best <- z
+ }
+ }
+ centers <- matrix(Z$centers, k)
+ dimnames(centers) <- list(1L:k, dimnames(x)[[2L]])
+ cluster <- Z$c1
+ if (!is.null(rn <- rownames(x)))
+ names(cluster) <- rn
+ totss <- sum(scale(x, scale = FALSE)^2)
+ print(Z$iter)
+ structure(list(cluster = cluster, centers = centers, totss = totss,
+ withinss = Z$wss, tot.withinss = best, betweenss = totss -
+ best, size = Z$nc, iter = Z$iter), class = "kmeans")
+ }
> <environment: namespace:stats>
Error: unexpected '<' in "<"
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