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:
genie_1.0.6.9001.tar.gz
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genie.pdf |genie.html✨
genie/json (API)
NEWS
# Install 'genie' in R: |
install.packages('genie', repos = c('https://gagolews.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gagolews/genie/issues
clustercluster-analysisclusteringdata-analysisdata-miningdata-sciencedatasciencegeniehierarchical-clustering-algorithmmachine-learningmachine-learning-algorithmsoutliers
Last updated 2 years agofrom:6a987ea3f5. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 03 2024 |
R-4.5-win-x86_64 | NOTE | Nov 03 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 03 2024 |
R-4.4-win-x86_64 | NOTE | Nov 03 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 03 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 03 2024 |
R-4.3-win-x86_64 | NOTE | Nov 03 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 03 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 03 2024 |
Exports:hclust2
Dependencies:genieclustRcpp
Readme and manuals
Help Manual
Help page | Topics |
---|---|
The Genie Package | genie-package genie |
Fast Hierarchical Clustering in Spaces Equipped With a Dissimilarity Measure | hclust2 |