Package: mixdir 0.3.0

mixdir: Cluster High Dimensional Categorical Datasets

Scalable Bayesian clustering of categorical datasets. The package implements a hierarchical Dirichlet (Process) mixture of multinomial distributions. It is thus a probabilistic latent class model (LCM) and can be used to reduce the dimensionality of hierarchical data and cluster individuals into latent classes. It can automatically infer an appropriate number of latent classes or find k classes, as defined by the user. The model is based on a paper by Dunson and Xing (2009) <doi:10.1198/jasa.2009.tm08439>, but implements a scalable variational inference algorithm so that it is applicable to large datasets. It is described and tested in the accompanying paper by Ahlmann-Eltze and Yau (2018) <doi:10.1109/DSAA.2018.00068>.

Authors:Constantin Ahlmann-Eltze [aut, cre], Christopher Yau [ths]

mixdir_0.3.0.tar.gz
mixdir_0.3.0.zip(r-4.5)mixdir_0.3.0.zip(r-4.4)mixdir_0.3.0.zip(r-4.3)
mixdir_0.3.0.tgz(r-4.4-x86_64)mixdir_0.3.0.tgz(r-4.4-arm64)mixdir_0.3.0.tgz(r-4.3-x86_64)mixdir_0.3.0.tgz(r-4.3-arm64)
mixdir_0.3.0.tar.gz(r-4.5-noble)mixdir_0.3.0.tar.gz(r-4.4-noble)
mixdir_0.3.0.tgz(r-4.4-emscripten)mixdir_0.3.0.tgz(r-4.3-emscripten)
mixdir.pdf |mixdir.html✨
mixdir/json (API)
NEWS

Peer review:

Bug tracker:https://github.com/const-ae/mixdir/issues

On CRAN:

categorical-dataclusteringquestionnairesvariational-inference

5 exports 14 stars 1.91 score 2 dependencies 1 mentions 22 scripts 148 downloads

Last updated 1 years agofrom:f772069f13. Checks:OK: 9. Indexed: yes.

Exports:find_defining_featuresfind_predictive_featuresfind_typical_featuresmixdirplot_features

Dependencies:extraDistrRcpp