Package: RJcluster 3.2.4
Rachael Shudde
RJcluster: A Fast Clustering Algorithm for High Dimensional Data Based on the Gram Matrix Decomposition
Clustering algorithm for high dimensional data. Assuming that P feature measurements on N objects are arranged in an N×P matrix X, this package provides clustering based on the left Gram matrix XX^T. To simulate test data, type "help('simulate_HD_data')" and to learn how to use the clustering algorithm, type "help('RJclust')". To cite this package, type 'citation("RJcluster")'.
Authors:
RJcluster_3.2.4.tar.gz
RJcluster_3.2.4.tar.gz(r-4.5-noble)RJcluster_3.2.4.tar.gz(r-4.4-noble)
RJcluster_3.2.4.tgz(r-4.4-emscripten)RJcluster_3.2.4.tgz(r-4.3-emscripten)
RJcluster.pdf |RJcluster.html✨
RJcluster/json (API)
| # Install 'RJcluster' in R: |
| install.packages('RJcluster', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:61d1046580. Checks:OK: 1 WARNING: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-linux-x86_64 | WARNING | Nov 20 2024 |
Exports:Mutual_InformationRJclustsimulate_HD_data
Dependencies:base64encbslibcachemclicodetoolsdigestevaluatefastmapfontawesomeforeachfsgluehighrhtmltoolshtmlwidgetsinfotheoiteratorsjquerylibjsonliteknitrlifecyclematrixStatsmclustmemoisemimeprofvisR6rappdirsRcppRcppArmadillorlangrmarkdownsasstinytexvctrsxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| A Fast Clustering Algorithm for High Dimensional Data Based on the Gram Matrix Decomposition | RJcluster-package RJcluster |
| Mutual_Information | Mutual_Information |
| RJclust | RJclust |
| simulate_HD_data | simulate_HD_data |
