Package: tglkmeans 0.5.7
Aviezer Lifshitz
tglkmeans: Efficient Implementation of K-Means++ Algorithm
Efficient implementation of K-Means++ algorithm. For more information see (1) "kmeans++ the advantages of the k-means++ algorithm" by David Arthur and Sergei Vassilvitskii (2007), Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, pp. 1027-1035, and (2) "The Effectiveness of Lloyd-Type Methods for the k-Means Problem" by Rafail Ostrovsky, Yuval Rabani, Leonard J. Schulman and Chaitanya Swamy <doi:10.1145/2395116.2395117>.
Authors:
tglkmeans_0.5.7.tar.gz
tglkmeans_0.5.7.tgz(r-4.4-x86_64)tglkmeans_0.5.7.tgz(r-4.4-arm64)tglkmeans_0.5.7.tgz(r-4.3-x86_64)tglkmeans_0.5.7.tgz(r-4.3-arm64)
tglkmeans_0.5.7.tar.gz(r-4.5-noble)tglkmeans_0.5.7.tar.gz(r-4.4-noble)
tglkmeans_0.5.7.tgz(r-4.4-emscripten)tglkmeans_0.5.7.tgz(r-4.3-emscripten)
tglkmeans.pdf |tglkmeans.html✨
tglkmeans/json (API)
NEWS
| # Install 'tglkmeans' in R: |
| install.packages('tglkmeans', repos = c('https://tanaylab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tanaylab/tglkmeans/issues
Last updated 5 months agofrom:c4c3f74c36. Checks:OK: 2 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 23 2024 |
| R-4.5-linux-x86_64 | OK | Nov 23 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 23 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 23 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 23 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 23 2024 |
Exports:%>%downsample_matrixsimulate_dataTGL_kmeansTGL_kmeans_tidytglkmeans.set_parallel
Dependencies:clicodetoolscolorspacedigestdoFuturedplyrfansifarverforeachfuturefuture.applygenericsggplot2globalsgluegtableisobanditeratorslabelinglatticelifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmeparallellypillarpkgconfigplyrpurrrR6RColorBrewerRcppRcppParallelrlangscalestgstattibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Downsample the columns of a matrix to a target number | downsample_matrix |
| Simulate normal data for kmeans tests | simulate_data |
| kmeans++ with return value similar to R kmeans | TGL_kmeans |
| TGL kmeans with 'tidy' output | TGL_kmeans_tidy |
| Set parallel threads | tglkmeans.set_parallel |
