Package: genieclust 1.3.0.9001
genieclust: Genie: Fast and Robust Hierarchical Clustering
Genie is a robust hierarchical clustering algorithm (Gagolewski, Bartoszuk, Cena, 2016 <doi:10.1016/j.ins.2016.05.003>). 'genieclust' is its faster, more capable implementation (Gagolewski, 2021 <doi:10.1016/j.softx.2021.100722>). It enables clustering with respect to mutual reachability distances, allowing it to act as an alternative to 'HDBSCAN*' that can identify any number of clusters or their entire hierarchy. When combined with the 'deadwood' package, it can act as an outlier detector. Additional package features include 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'.
Authors:
genieclust_1.3.0.9001.tar.gz
genieclust_1.3.0.9001.zip(r-4.7)genieclust_1.3.0.9001.zip(r-4.6)genieclust_1.3.0.9001.zip(r-4.5)
genieclust_1.3.0.9001.tgz(r-4.6-x86_64)genieclust_1.3.0.9001.tgz(r-4.6-arm64)genieclust_1.3.0.9001.tgz(r-4.5-x86_64)genieclust_1.3.0.9001.tgz(r-4.5-arm64)
genieclust_1.3.0.9001.tar.gz(r-4.7-arm64)genieclust_1.3.0.9001.tar.gz(r-4.7-x86_64)genieclust_1.3.0.9001.tar.gz(r-4.6-arm64)genieclust_1.3.0.9001.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
genieclust/json (API)
NEWS
| # Install 'genieclust' in R: |
| install.packages('genieclust', repos = c('https://gagolews.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gagolews/genieclust/issues
cluster-analysisclusteringclustering-algorithmdata-analysisdata-miningdata-sciencegeniehdbscanhierarchical-clusteringhierarchical-clustering-algorithmmachine-learningmachine-learning-algorithmsmlpacknmslibpythonpython3sparsecpp
Last updated from:fbb934c540. Checks:12 OK, 1 FAIL. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 115 | ||
| linux-devel-x86_64 | OK | 111 | ||
| source / vignettes | OK | 206 | ||
| linux-release-arm64 | OK | 112 | ||
| linux-release-x86_64 | OK | 110 | ||
| macos-release-arm64 | OK | 83 | ||
| macos-release-x86_64 | OK | 184 | ||
| macos-oldrel-arm64 | OK | 86 | ||
| macos-oldrel-x86_64 | OK | 211 | ||
| windows-devel | OK | 161 | ||
| windows-release | OK | 127 | ||
| windows-oldrel | OK | 93 | ||
| wasm-release | FAIL | 92 |
Exports:adjusted_fm_scoreadjusted_mi_scoreadjusted_rand_scorebonferroni_indexcalinski_harabasz_indexdevergottini_indexdunnowa_indexfm_scoregclustgeneralised_dunn_indexgeniegini_indexmi_scorenegated_ball_hall_indexnegated_davies_bouldin_indexnegated_wcss_indexnormalized_clustering_accuracynormalized_confusion_matrixnormalized_mi_scorenormalized_pivoted_accuracynormalizing_permutationpair_sets_indexrand_scoresilhouette_indexsilhouette_w_indexwcnn_index
Dependencies:deadwoodquitefastmstRcpp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Internal Cluster Validity Measures | calinski_harabasz_index cluster_validity dunnowa_index generalised_dunn_index negated_ball_hall_index negated_davies_bouldin_index negated_wcss_index silhouette_index silhouette_w_index wcnn_index |
| External Cluster Validity Measures and Pairwise Partition Similarity Scores | adjusted_fm_score adjusted_mi_score adjusted_rand_score compare_partitions fm_score mi_score normalized_clustering_accuracy normalized_confusion_matrix normalized_mi_score normalized_pivoted_accuracy normalizing_permutation pair_sets_index rand_score |
| Hierarchical Clustering Algorithm Genie | gclust gclust.default gclust.dist gclust.mst genie genie.default genie.dist genie.mst |
| Inequality Measures | bonferroni_index devergottini_index gini_index inequality |
