A C++ implementation of the Silhouette method of interpretation and validation of consistency within acca clusters of data.
Usage
sil_acca(acca, ...)
# S3 method for acca_list
sil_acca(acca, m, ...)
# S3 method for list
sil_acca(acca, m, ...)Arguments
- acca
\[
acca_list(1)]
Acca clustering results fromacca- ...
Additional arguments (TODO).
- m
\[
matrix(1)]
correlation matrix fromcorr_matrix. By default the distance matrix(dist) used in this method is given by `dist = 1 - m`.
Value
\[numeric(1)]
the average value of
the silhouette width over all data of the entire dataset.
Observations with a large average silhouette width (almost 1)
are very well clustered.
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.