pintervals (version 1.0.1)

optimize_clusters: Function to optimize clusters based on the Calinski-Harabasz index

Description

Function to optimize clusters based on the Calinski-Harabasz index

Usage

optimize_clusters(
  ncs,
  class_vec,
  method = c("ks", "kmeans"),
  min_m = 2,
  max_m = NULL,
  ms = NULL,
  maxit = 100,
  q = seq(0.1, 0.9, by = 0.1)
)

Value

A vector of cluster assignments, with attributes containing the clusters, coverage gaps, method used, number of clusters, and the Calinski-Harabasz index

Arguments

ncs

Vector of non-conformity scores

class_vec

Vector of class labels

method

Clustering method to use, either 'ks' for Kolmogorov-Smirnov or 'kmeans' for K-means clustering

min_m

Minimum number of clusters to consider

max_m

Maximum number of clusters to consider. If NULL, defaults to the number of unique classes minus one

ms

Vector of specific numbers of clusters to consider. If NULL, defaults to a sequence from min_m to max_m

maxit

Maximum number of iterations for the clustering algorithm

q

Quantiles to use for K-means clustering, default is a sequence from 0.1 to 0.9 in steps of 0.1