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pfclust  

Power Fuzzy Clustering and Cluster-Wise Regression
View on CRAN: Click here


Download and install pfclust package within the R console
Install from CRAN:
install.packages("pfclust")

Install from Github:
library("remotes")
install_github("cran/pfclust")

Install by package version:
library("remotes")
install_version("pfclust", "0.1.0")



Attach the package and use:
library("pfclust")
Maintained by
Phuc Thinh Nguyen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-28
Latest Update: 2026-04-28
Description:
Implementations of Power Fuzzy Clustering (PFC) and Power Fuzzy Cluster-wise Regression (PFCR) for multivariate data. The package supports Minkowski distances, with the L1 case solved via iteratively re-weighted least squares and the case p > 1 solved via coordinate-wise root finding, as well as an adaptive, regularised Mahalanobis distance with per-cluster covariance matrices. Both plain fuzzy clustering and cluster-wise linear regression are provided. The corresponding paper can be found at Nguyen P.T., Tortora C., and Punzo A. (2026) <doi:10.1109/TFUZZ.2026.3683998>.
How to cite:
Phuc Thinh Nguyen (2026). pfclust: Power Fuzzy Clustering and Cluster-Wise Regression. R package version 0.1.0, https://cran.r-project.org/web/packages/pfclust. Accessed 30 Jul. 2026.
Previous versions and publish date:
(2026-07-13 23:50), 0.1.0 (2026-04-28 20:20)
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Complete documentation for pfclust
Functions, R codes and Examples using the pfclust R package
Full pfclust package functions and examples
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