Package: genie 1.0.6.9001

genie: Fast, Robust, and Outlier Resistant Hierarchical Clustering

Includes the reference implementation of Genie - a hierarchical clustering algorithm that links two point groups in such a way that an inequity measure (namely, the Gini index) of the cluster sizes does not significantly increase above a given threshold. This method most often outperforms many other data segmentation approaches in terms of clustering quality as tested on a wide range of benchmark datasets. At the same time, Genie retains the high speed of the single linkage approach, therefore it is also suitable for analysing larger data sets. For more details see (Gagolewski et al. 2016 <doi:10.1016/j.ins.2016.05.003>). For an even faster and more feature-rich implementation, including, amongst others, noise point detection, see the 'genieclust' package (Gagolewski, 2021 <doi:10.1016/j.softx.2021.100722>).

Authors:Marek Gagolewski [aut, cre, cph], Maciej Bartoszuk [aut], Anna Cena [aut]

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genie/json (API)
NEWS

# Install 'genie' in R:
install.packages('genie', repos = c('https://gagolews.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/gagolews/genie/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

clustercluster-analysisclusteringdata-analysisdata-miningdata-sciencedatasciencegeniehierarchical-clustering-algorithmmachine-learningmachine-learning-algorithmsoutliers

4.55 score 22 stars 16 scripts 250 downloads 1 exports 2 dependencies

Last updated 2 years agofrom:6a987ea3f5. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-win-x86_64NOTENov 03 2024
R-4.5-linux-x86_64NOTENov 03 2024
R-4.4-win-x86_64NOTENov 03 2024
R-4.4-mac-x86_64NOTENov 03 2024
R-4.4-mac-aarch64NOTENov 03 2024
R-4.3-win-x86_64NOTENov 03 2024
R-4.3-mac-x86_64NOTENov 03 2024
R-4.3-mac-aarch64NOTENov 03 2024

Exports:hclust2

Dependencies:genieclustRcpp