best_acca: Silhouette (clustering)

In meantrix/corrP: corrp (Compute correlations type analysis in parallel)

Silhouette (clustering)

Description

Determining the optimal number of cluster in the ACCA clustering using the average silhouette aproach.

Usage

best_acca(m, ...)

## S3 method for class 'cmatrix'
best_acca(m, mink, maxk, maxrep = 2L, maxiter = 100L, ...)

## S3 method for class 'matrix'
best_acca(m, mink, maxk, maxrep = 2L, maxiter = 100L, ...)

Arguments

m	\[matrix(1)] correlation matrix from corr_matrix.
...	Additional arguments (TODO).
mink	\[integer(1)] minimum number of clusters considered.
maxk	\[integer(1)] maximum number of clusters considered.
maxrep	\[integer(1)] maximum number of interactions without change in the clusters in the ACCA method.
maxiter	\[integer(1)] maximum number of interactions in the ACCA method.

Value

\[list(3)]
A list with: silhouette average with per k '$silhouette.ave'; the sequence of clusters tested '$k' and the optimal number of clusters '$best.k'.

Author(s)

Igor D.S. Siciliani

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.

See Also

sil_acca

Examples

## Not run: 

x = corrp::corrp(iris)
m = corrp::corr_matrix(x)
best_acca(m,2,6)


## End(Not run)

meantrix/corrP documentation built on Oct. 22, 2024, 10:16 a.m.