The Genie algorithm (Gagolewski, 2021 <doi:10.1016/j.softx.2021.100722>) is a robust and outlier-resistant hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 <doi:10.1016/j.ins.2016.05.003>). This package features its faster and more powerful version. It allows clustering with respect to mutual reachability distances, enabling it to act as a noise point detector or a version of 'HDBSCAN*' that can identify a predefined number of clusters. The package also features an implementation of the Gini and Bonferroni inequality indices, external cluster validity measures (e.g., the normalised clustering accuracy, the adjusted Rand index, the Fowlkes-Mallows index, and normalised mutual information), and internal cluster validity indices (e.g., the Calinski-Harabasz, Davies-Bouldin, Ball-Hall, Silhouette, and generalised Dunn indices). The 'Python' version of 'genieclust' is available via 'PyPI'.
Version: 1.2.0 Imports: Rcpp, stats, utils, quitefastmst LinkingTo: Rcpp Suggests: datasets Published: 2025-07-24 DOI: 10.32614/CRAN.package.genieclust Author: Marek Gagolewski [aut, cre, cph], Maciej Bartoszuk [ctb], Anna Cena [ctb], Peter M. Larsen [ctb] Maintainer: Marek Gagolewski <marek at gagolewski.com> BugReports: https://github.com/gagolews/genieclust/issues License: AGPL-3 URL: https://genieclust.gagolewski.com/, https://clustering-benchmarks.gagolewski.com/, https://github.com/gagolews/genieclust NeedsCompilation: yes SystemRequirements: OpenMP, C++17 Citation: genieclust citation info Materials: NEWS In views: Cluster CRAN checks: genieclust results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=genieclust to link to this page.
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