CritCF.sel: Number of cluster selection according to 'CritCF' index
In LilithF/doMIsaul: Do Multiple Imputation-Based Semi-Supervised and Unsupervised Learning

Wrapper to estimate the best number of clusters according to CritCF index

1	CritCF.sel(data, min.nc, max.nc, method, distance)

`data`	dataframe for which the number of cluster should be estimated.
`min.nc`	integer strictly higher than 1: minimum number of clusters.
`max.nc`	integer (`>min.nc`): maximum number of clusters.
`method`	string, clustering algorithm to use. Available values are "`kmeans`", "`hc`" (for `hclust()`) or "`mclust`".
`distance`	string, distance between the observations (either "euclidean" or "manhattan").

A list containing the selected number of clusters, the CritCF values and the best partition.

LilithF/doMIsaul documentation built on Dec. 17, 2021, 12:08 a.m.

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