partition_generation: Unsupervised partition with K selection

In LilithF/doMIsaul: Do Multiple Imputation-Based Semi-Supervised and Unsupervised Learning

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

partition_generation(iris[, 1:4], LOG = FALSE,
                     clust.algo = c("km", "hc"), k.crit = "ch")

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