Package: kamila 0.1.2
kamila: Methods for Clustering Mixed-Type Data
Implements methods for clustering mixed-type data, specifically combinations of continuous and nominal data. Special attention is paid to the often-overlooked problem of equitably balancing the contribution of the continuous and categorical variables. This package implements KAMILA clustering, a novel method for clustering mixed-type data in the spirit of k-means clustering. It does not require dummy coding of variables, and is efficient enough to scale to rather large data sets. Also implemented is Modha-Spangler clustering, which uses a brute-force strategy to maximize the cluster separation simultaneously in the continuous and categorical variables. For more information, see Foss, Markatou, Ray, & Heching (2016) <doi:10.1007/s10994-016-5575-7> and Foss & Markatou (2018) <doi:10.18637/jss.v083.i13>.
Authors:
kamila_0.1.2.tar.gz
kamila_0.1.2.zip(r-4.5)kamila_0.1.2.zip(r-4.4)kamila_0.1.2.zip(r-4.3)
kamila_0.1.2.tgz(r-4.4-x86_64)kamila_0.1.2.tgz(r-4.4-arm64)kamila_0.1.2.tgz(r-4.3-x86_64)kamila_0.1.2.tgz(r-4.3-arm64)
kamila_0.1.2.tar.gz(r-4.5-noble)kamila_0.1.2.tar.gz(r-4.4-noble)
kamila_0.1.2.tgz(r-4.4-emscripten)kamila_0.1.2.tgz(r-4.3-emscripten)
kamila.pdf |kamila.html✨
kamila/json (API)
# Install 'kamila' in R: |
install.packages('kamila', repos = c('https://ahfoss.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ahfoss/kamila/issues
Last updated 1 years agofrom:af50489d10. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-win-x86_64 | OK | Nov 04 2024 |
R-4.5-linux-x86_64 | OK | Nov 04 2024 |
R-4.4-win-x86_64 | OK | Nov 04 2024 |
R-4.4-mac-x86_64 | OK | Nov 04 2024 |
R-4.4-mac-aarch64 | OK | Nov 04 2024 |
R-4.3-win-x86_64 | OK | Nov 04 2024 |
R-4.3-mac-x86_64 | OK | Nov 04 2024 |
R-4.3-mac-aarch64 | OK | Nov 04 2024 |
Exports:classifyKamiladptmCppdummyCodeFactorDfgenMixedDatagmsClustkamilawkmeans
Dependencies:abindgtoolsKernSmoothplyrRcpp