sil_acca: Silhouette (Clustering)

In meantrix/corrP: Compute Correlations Type Analysis in Parallel

Silhouette (Clustering)

Description

A C++ implementation of the Silhouette method for interpreting and validating consistency within acca clusters of data.

Usage

sil_acca(acca, m, ...)

## S3 method for class 'acca_list'
sil_acca(acca, m, ...)

## S3 method for class 'list'
sil_acca(acca, m, ...)

Arguments

acca	[acca_list(1)] Acca clustering results from acca.
m	[cmatrix(1)|matrix(1)] A correlation matrix from corr_matrix. By default, the distance matrix (dist) used in this method is given by dist = 1 - m.
...	Additional arguments.

Value

[numeric(1)]
The average value of the silhouette width across all data in the entire dataset. Observations with a large average silhouette width (close to 1) are very well clustered.

Author(s)

Igor D.S. Siciliani, Paulo H. dos Santos

References

Leonard Kaufman; Peter J. Rousseeuw (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Hoboken, NJ: Wiley-Interscience. p. 87. doi:10.1002/9780470316801. ISBN 9780471878766.

Starczewski, Artur, and Adam Krzyżak. "Performance Evaluation of the Silhouette Index." International Conference on Artificial Intelligence and Soft Computing. Springer, Cham, 2015.

Examples

x <- corrp::corrp(iris)
m <- corrp::corr_matrix(x)
acca <- corrp::acca(m, 2)
sil_acca(acca, m)

meantrix/corrP documentation built on June 12, 2025, 5:33 p.m.