compute_gapstat: Compute Gap statistic for clustered data

In visxhclust: A Shiny App for Visual Exploration of Hierarchical Clustering

Compute Gap statistic for clustered data

Description

Compute Gap statistic for clustered data

Usage

compute_gapstat(df, clusters, gap_B = 50, max_k = 14)

Arguments

df	the data used to compute clusters
clusters	output of compute_clusters() or fastcluster::hclust()
gap_B	number of bootstrap samples for cluster::clusGap() function. Default is 50.
max_k	maximum number of clusters to compute the statistic. Default is 14.

Value

a data frame with the Tab component of cluster::clusGap() results

Examples

data_to_cluster <- iris[c("Petal.Length", "Sepal.Length")]
dmat <- compute_dmat(data_to_cluster, "euclidean", TRUE)
clusters <- compute_clusters(dmat, "complete")
gap_results <- compute_gapstat(scale(data_to_cluster), clusters)
head(gap_results)

visxhclust documentation built on March 31, 2023, 7:30 p.m.