R: Run Flexclust Algorithms Repeatedly

stepFlexclust {flexclust} | R Documentation

## Run Flexclust Algorithms Repeatedly

### Description

Runs clustering algorithms repeatedly for different numbers of clusters and returns the minimum within cluster distance solution for each.

### Usage

    stepFlexclust(x, k, nrep=3, verbose=TRUE, FUN = kcca, drop=TRUE,
                  group=NULL, simple=FALSE, save.data=FALSE, seed=NULL,
                  multicore=TRUE, ...)

    stepcclust(...)

    ## S4 method for signature 'stepFlexclust,missing'
    plot(x, y,
      type=c("barplot", "lines"), totaldist=NULL,
      xlab=NULL, ylab=NULL, ...)

    ## S4 method for signature 'stepFlexclust'
    getModel(object, which=1)

### Arguments

`x, ...` | Passed to `kcca` or `cclust`.
`k` | A vector of integers passed in turn to the `k` argument of `kcca`
`nrep` | For each value of `k` run `kcca` `nrep` times and keep only the best solution.
`FUN` | Cluster function to use, typically `kcca` or `cclust`.
`verbose` | If `TRUE`, show progress information during computations.
`drop` | If `TRUE` and `K` is of length 1, then a single cluster object is returned instead of a `"stepFlexclust"` object.
`group` | An optional grouping vector for the data, see `kcca` for details.
`simple` | Return an object of class `"kccasimple"`?
`save.data` | Save a copy of `x` in the return object?
`seed` | If not `NULL`, a call to `set.seed()` is made before any clustering is done.
`multicore` | If `TRUE`, use `mclapply()` from package parallel for parallel processing.
`y` | Not used.
`type` | Create a barplot or lines plot.
`totaldist` | Include value for 1-cluster solution in plot? Default is `TRUE` if `K` contains `2`, else `FALSE`.
`xlab, ylab` | Graphical parameters.
`object` | Object of class `"stepFlexclust"`.
`which` | Number of model to get. If character, interpreted as number of clusters.

### Details

`stepcclust` is a simple wrapper for `stepFlexclust(...,FUN=cclust)`.

### Author(s)

Friedrich Leisch

### Examples

    data("Nclus")
    plot(Nclus)

    ## multicore off for CRAN checks
    cl1 <- stepFlexclust(Nclus, k=2:7, FUN=cclust, multicore=FALSE)
    cl1

    plot(cl1)

    # two ways to do the same:
    getModel(cl1, 4)
    cl1[[4]]

    opar <- par("mfrow")
    par(mfrow=c(2, 2))
    for(k in 3:6){
      image(getModel(cl1, as.character(k)), data=Nclus)
      title(main=paste(k, "clusters"))
    }
    par(opar)

[Package flexclust version 1.4-1 Index]