genieclust: Fast and Robust Hierarchical Clustering with Noise Points Detection

A retake on the Genie algorithm (Gagolewski, 2021 <doi:10.1016/j.softx.2021.100722>) - a robust hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 <doi:10.1016/j.ins.2016.05.003>). Now faster and more memory efficient; determining the whole hierarchy for datasets of 10M points in low dimensional Euclidean spaces or 100K points in high-dimensional ones takes only 1-2 minutes. Allows clustering with respect to mutual reachability distances so that it can act as a noise point detector or a robustified version of 'HDBSCAN*' (that is able to detect a predefined number of clusters and hence it does not dependent on the somewhat fragile 'eps' parameter). The package also features an implementation of economic inequity indices (the Gini, Bonferroni index), external cluster validity measures (e.g., the adjusted asymmetric accuracy and partition similarity scores such as the adjusted Rand, Fowlkes-Mallows, adjusted mutual information, and pair sets indices), and internal cluster validity indices (e.g., the Calinski-Harabasz, Davies-Bouldin, Ball-Hall, Silhouette, and generalised Dunn indices). See also the 'Python' version of 'genieclust' available on 'PyPI', which supports sparse data, more metrics, and even larger datasets.

Version: 1.1.0
Imports: Rcpp (≥ 1.0.4), stats, utils
LinkingTo: Rcpp
Suggests: datasets, mlpack
Published: 2022-09-05
Author: Marek Gagolewski ORCID iD [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++11
Citation: genieclust citation info
Materials: NEWS
In views: Cluster
CRAN checks: genieclust results

Documentation:

Reference manual: genieclust.pdf

Downloads:

Package source: genieclust_1.1.0.tar.gz
Windows binaries: r-devel: genieclust_1.1.0.zip, r-release: genieclust_1.1.0.zip, r-oldrel: genieclust_1.1.0.zip
macOS binaries: r-release (arm64): genieclust_1.1.0.tgz, r-oldrel (arm64): genieclust_1.1.0.tgz, r-release (x86_64): genieclust_1.1.0.tgz, r-oldrel (x86_64): genieclust_1.1.0.tgz
Old sources: genieclust archive

Reverse dependencies:

Reverse depends: genie
Reverse imports: Kmedians, RGMM

Linking:

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