Clarified the description of the PAC (Proportion of Ambiguous Clustering) method in the documentation by citing the original authors (Author, Year).
Removed usage of installed.packages()
from the
package code and replaced it with a more robust and CRAN-compliant
approach, following suggested practices.
All user-facing functions now include the argument
print.summary
, which controls whether summary details are
printed. This argument behaves similarly to
if (verbose) cat(...)
and now defaults to
FALSE
.
Messages using message()
are included in example
sections to suggest installation of optional packages
(e.g., ppclust
, blockcluster
). These packages
are not called directly, but their outputs are used in
examples. This is done to guide users without violating CRAN’s policy on
requiring packages in examples.
Removed the license file as suggested.
Initial Stable Release
The first stable release of the Silhouette package, offering tools to compute and visualize silhouette widths for evaluating clustering quality. It supports both crisp and soft clustering outputs, along with multi-way clustering (e.g., biclustering).
Silhouette()
Computes silhouette widths using proximity matrices (dissimilarity or
similarity). Supports "medoid"
and "pac"
normalization methods, and fuzzy silhouette calculation via membership
probabilities.
softSilhouette()
Tailored for soft clustering. Transforms membership probabilities into
proximity measures (posterior probabilities, negative log-probabilities,
or raw distributions) before silhouette computation.
extSilhouette()
Extends silhouette analysis to multi-way clustering (e.g., biclustering
or triclustering) by aggregating silhouette widths across modes,
weighted by observation counts.
plotSilhouette()
Creates detailed silhouette plots using ggplot2, with
options for grayscale themes, cluster-wise summaries, and labeled
observations. Compatible with outputs from Silhouette
,
softSilhouette
, and popular packages like
cluster and factoextra.
summary.Silhouette()
Summarizes silhouette results, including average silhouette widths per
cluster and overall summary statistics.
dplyr
, ggplot2
,
ggpubr
, methods
proxy
, ppclust
,
blockcluster
, cluster
,
factoextra