This package is considered a duplicate. The official version of this package is found at:https://andrewthomasjones.r-universe.dev/lowmemtkmeans
Package: lowmemtkmeans 0.1.2
Andrew Thomas Jones
lowmemtkmeans: Low Memory Use Trimmed K-Means
Performs the trimmed k-means clustering algorithm with lower memory use. It also provides a number of utility functions such as BIC calculations.
Authors:
lowmemtkmeans_0.1.2.tar.gz
lowmemtkmeans_0.1.2.tar.gz(r-4.5-noble)lowmemtkmeans_0.1.2.tar.gz(r-4.4-noble)
lowmemtkmeans_0.1.2.tgz(r-4.4-emscripten)lowmemtkmeans_0.1.2.tgz(r-4.3-emscripten)
lowmemtkmeans.pdf |lowmemtkmeans.html✨
lowmemtkmeans/json (API)
NEWS
| # Install 'lowmemtkmeans' in R: |
| install.packages('lowmemtkmeans', 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 8 years agofrom:d282f53ee2. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 27 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 27 2024 |
Exports:cluster_BICnearest_clusterscale_mat_inplacetkmeans
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculates BIC for a given clustering. | cluster_BIC |
| Allocates each rw (observation) in data to the nearest cluster centre. | nearest_cluster |
| Rescales a matrix in place. | scale_mat_inplace |
| Trimmed k-means clustering | tkmeans |
