Package: fcmfd 0.1.1

José Ortigas

fcmfd: Fuzzy C-Means for Fuzzy Data

Implements a fuzzy clustering approach for ordinal Likert-type data using triangular fuzzy numbers (TFNs). The package extends the classical fuzzy C-means algorithm to better handle uncertainty in ordinal scales and includes automatic selection of the number of clusters using the Xie-Beni validity index. References: Coppi, R., D'Urso, P., and Giordani, P. (2012), "Fuzzy and possibilistic clustering for fuzzy data", <doi:10.1016/j.csda.2010.09.013>. Xie, X. L. and Beni, G. (1991), "A validity measure for fuzzy clustering", <doi:10.1109/34.85677>.

Authors:José Ortigas [aut, cre]

fcmfd_0.1.1.tar.gz
fcmfd_0.1.1.tar.gz(r-4.7-any)fcmfd_0.1.1.tar.gz(r-4.6-any)
fcmfd_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
fcmfd/json (API)
NEWS

# Install 'fcmfd' in R:
install.packages('fcmfd', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.00 score 388 downloads 8 exports 0 dependencies

Last updated from:62465c786f. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK170
source / vignettesOK197
linux-release-x86_64OK169
wasm-releaseOK96

Exports:cluster_assignmentfcmTFNmembershipplot_dictionaryplot_prototypesplot_xbprint_fcmTFNprototype_matrix

Dependencies:

Introduction to fcmfd

Rendered fromfcmTFN-introduction.Rmdusingknitr::rmarkdownon Jun 22 2026.

Last update: 2026-05-05
Started: 2026-05-05