Calculate Starting Values for Fuzzy k-means Clustering

Description

This function calculates starting values as used in the wrapFKM function.

Usage

1
getStart(d, K = 10, nrep = 100, safety = TRUE, ...)

Arguments

d

data-set with standardized columns

K

number of clusters

nrep

number of repetitions for the call to kmeans (default is 100).

safety

As described in the help to kmeans, the algorithm may not converge in the quick-transfer stage. If safety is set to TRUE, each run where this happens is discarded and repeated from a different random starting point.

...

further arguments to kmeans.

Details

This function calculates starting values for wrapFKM as the solution of k-means clustering.

Value

A matrix with K columns and nrow(d) rows.

Author(s)

Holger Sennhenn-Reulen

Examples

1
## Not run: getStart(d, K = 10, nrep = 100, safety = TRUE, ...)