ClusterCV: Estimating Number of Cluster with Gabriel Cross-validation

In pangoria/clusterEstimation: Estimating Cluster with Gabriel Cross Validation

Description

This function determines the number of clusters using Gabriel cross-validation, with the option of using an adjustment for when dimensional correlation is high.

Usage

ClusterCV(
  input.data,
  kclust.min,
  kclust.max,
  nfold.r,
  nfold.c,
  adjusted = F,
  alg = "k.means"
)

Arguments

input.data	data matrix
kclust.min	minimum number of clusters
kclust.max	maximum number of clusters
nfold.r	number of folds row-wise
nfold.c	number of folds column-wise
adjusted	T/F, default is FALSE
alg	clustering algorithm used k-means or spectral, with k-means as the default

Value

Returns a list of the final estimation of the number of clusters that minimizes the cross-validation error and the cluster assignments for each observation.

pangoria/clusterEstimation documentation built on Dec. 22, 2021, 6:39 a.m.