<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>ghashti-j.r-universe.dev</title><link>https://ghashti-j.r-universe.dev</link><description>Recent package updates in ghashti-j</description><generator>R-universe</generator><image><url>https://github.com/ghashti-j.png</url><title>R packages by ghashti-j</title><link>https://ghashti-j.r-universe.dev</link></image><lastBuildDate>Thu, 20 Aug 2026 01:44:06 GMT</lastBuildDate><item><title>[ghashti-j] FITclust 1.0.0</title><author>jesse.ghashti@ubc.ca (Jesse S. Ghashti)</author><description>Implementation of Fair Interpolated Transport (FIT), an
algorithm-agnostic preprocessing framework for group-fair
clustering. Group-conditional empirical distributions are moved
along Wasserstein-2 geodesics toward a shared barycenter at a
tunable transport intensity, and the smallest intensity meeting
a soft-fairness tolerance is selected. Three soft clustering
families are provided, centroid based, graph based, and model
based.</description><link>https://github.com/r-universe/ghashti-j/actions/runs/35584645610</link><pubDate>Thu, 20 Aug 2026 01:44:06 GMT</pubDate><r:package>FITclust</r:package><r:version>1.0.0</r:version><r:status>success</r:status><r:repository>https://ghashti-j.r-universe.dev</r:repository><r:upstream>https://github.com/ghashti-j/fitclust</r:upstream><r:article><r:source>FITclust.Rmd</r:source><r:filename>FITclust.html</r:filename><r:title>Fair Interpolated Transport for Group-Fair Clustering</r:title><r:created>2026-08-20 01:41:16</r:created><r:modified>2026-08-20 01:41:16</r:modified></r:article></item><item><title>[ghashti-j] FuzzySpec 1.0.0</title><author>jesse.ghashti@ubc.ca (Jesse S. Ghashti)</author><description>Implementation of the FVIBES, the Fuzzy
Variable-Importance Based Eigenspace Separation algorithm as
described in the paper by Ghashti, J.S., Hare, W., and J.R.J.
Thompson (2025). Variable-Weighted Adjacency Constructions for
Fuzzy Spectral Clustering. Submitted.</description><link>https://github.com/r-universe/ghashti-j/actions/runs/37286756395</link><pubDate>Thu, 08 Jan 2026 00:05:54 GMT</pubDate><r:package>FuzzySpec</r:package><r:version>1.0.0</r:version><r:status>success</r:status><r:repository>https://ghashti-j.r-universe.dev</r:repository><r:upstream>https://github.com/ghashti-j/fuzzyspec</r:upstream><r:article><r:source>FuzzySpec.Rmd</r:source><r:filename>FuzzySpec.html</r:filename><r:title>Fuzzy Spectral Clustering with Variable-Weighted Adjacency Matrices</r:title><r:created>2025-09-25 19:49:56</r:created><r:modified>2025-10-04 21:22:25</r:modified></r:article></item><item><title>[ghashti-j] bootkmeans 1.0.0</title><author>jesse.ghashti@ubc.ca (Jesse S. Ghashti)</author><description>Implementation of the bootkmeans algorithm, a bootstrap
augmented k-means algorithm that returns probabilistic cluster
assignments. From paper by Ghashti, J.S., Andrews, J.L.
Thompson, J.R.J., Epp, J. and H.S. Kochar (2025), &quot;A bootstrap
augmented k-means algorithm for fuzzy partitions&quot; (Submitted).</description><link>https://github.com/r-universe/ghashti-j/actions/runs/38126812638</link><pubDate>Fri, 10 Oct 2025 21:47:39 GMT</pubDate><r:package>bootkmeans</r:package><r:version>1.0.0</r:version><r:status>success</r:status><r:repository>https://ghashti-j.r-universe.dev</r:repository><r:upstream>https://github.com/ghashti-j/bootkmeans</r:upstream><r:article><r:source>bootkmeans.Rmd</r:source><r:filename>bootkmeans.html</r:filename><r:title>bootkmeans: Bootstrap Augmented k-Means Algorithm for Parameter-less Fuzzy Clustering</r:title><r:created>2025-09-26 22:46:36</r:created><r:modified>2025-10-04 21:23:28</r:modified></r:article></item></channel></rss>