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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>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats |
| Suggests: | flexCWM |
| Published: | 2026-04-28 |
| DOI: | 10.32614/CRAN.package.pfclust |
| Author: | Phuc Thinh Nguyen [aut, cre], Cristina Tortora [aut, ths, dgs], Antonio Punzo [aut, ths, dgs] |
| Maintainer: | Phuc Thinh Nguyen <phucthinh010603 at yahoo.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | pfclust results |
| Reference manual: | pfclust.html , pfclust.pdf |
| Package source: | pfclust_0.1.0.tar.gz |
| Windows binaries: | r-devel: pfclust_0.1.0.zip, r-release: pfclust_0.1.0.zip, r-oldrel: pfclust_0.1.0.zip |
| macOS binaries: | r-release (arm64): pfclust_0.1.0.tgz, r-oldrel (arm64): pfclust_0.1.0.tgz, r-release (x86_64): pfclust_0.1.0.tgz, r-oldrel (x86_64): pfclust_0.1.0.tgz |
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