clustQual: Cluster Quality
In zrmacc/MGMM: Missingness Aware Gaussian Mixture Models

ClustQual

R Documentation

Cluster Quality

Description

Evaluates cluster quality. Returns the following metrics:

BIC: Bayesian Information Criterion, lower value indicates better clustering quality.
CHI: Calinski-Harabaz Index, higher value indicates better clustering quality.
DBI: Davies-Bouldin, lower value indicates better clustering quality.
SIL: Silhouette Width, higher value indicates better clustering quality.

Usage

ClustQual(fit)

Arguments

fit

Object of class mix.

Value

List containing the cluster quality metrics.

Examples

set.seed(100)

# Data generation
mean_list = list(
c(2, 2, 2),
c(-2, 2, 2),
c(2, -2, 2),
c(2, 2, -2)
)

data <- rGMM(n = 500, d = 3, k = 4, means = mean_list)
fit <- FitGMM(data, k = 4)

# Clustering quality
cluster_qual <- ClustQual(fit)

zrmacc/MGMM documentation built on April 29, 2023, 10:17 p.m.