doMIsaul (version 1.0.1)

partition_generation: Unsupervised partition with K selection

Description

Generates a partition using clust.algo algorithm, with k.crit for selecting the number of clusters

Usage

partition_generation(data, LOG, clust.algo, k.crit)

Arguments

data

dataframe to cluster

LOG

logical. Should all columns of the dataset be logged before applying clustering algorithms?

clust.algo

vector of strings: name of clustering algorithms to use (use "km" for k-means, "kmed" for K-medians, "hc" for hclust() and/or "mclust" for mclust()).

k.crit

string. Criterion to select the optimal number of clusters (for each imputed dataset). Use "ch" for Calinski and Harabasz criterion (not available for "mclust"), "CritCF" for CritCF or bic for BIC ("mclust" only).

Value

a dataframe with one column for each algorithm in clust.algo, containing the cluster IDs.

Examples

# NOT RUN {
partition_generation(iris[, 1:4], LOG = FALSE,
                     clust.algo = c("km", "hc"), k.crit = "ch")
# }