CKMSelNo: The current function calculates the Cardinality KMeans (i.e....

In syuanuvt/CKM: Cardinality KM - simultaneous clustering and variable selection

The current function calculates the Cardinality KMeans (i.e. CKM) solution, without selecting the number of masking variables and clusters (they are assumed known)

Description

The current function calculates the Cardinality KMeans (i.e. CKM) solution, without selecting the number of masking variables and clusters (they are assumed known)

Usage

CKMSelNo(dataset, n.cluster, n.noisevar, num_starts_kmeans = 10)

Arguments

dataset	the orginal dataset on which CKM operates
n.cluster	the total number of clusters
n.noisevar	the total number of masking variables
num_starts_kmeans	the number of starts for the conventional KM analysis (note that in CKM, the conventional KM operates in the lower dimensions). The default value is 10

Value

@return The function will return a ckm object that is the list of five elements. The first denotes the selected number of masking variables; the second includes all indicies of signaling variables; the third is a vector illustrating cluster assignment; the forth is the pre-determined or selected "optimal" number of clusters; the fifth is the original dataset.

Examples

ncluster <- 3
nnoisevar <- 100
ckm.sel.no <- CKMSelNo(dataset, ncluster, nnoisevar)

syuanuvt/CKM documentation built on Dec. 1, 2022, 9:06 p.m.