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mixdir  

Cluster High Dimensional Categorical Datasets
View on CRAN: Click here


Download and install mixdir package within the R console
Install from CRAN:
install.packages("mixdir")

Install from Github:
library("remotes")
install_github("cran/mixdir")

Install by package version:
library("remotes")
install_version("mixdir", "0.3.0")



Attach the package and use:
library("mixdir")
Maintained by
Constantin Ahlmann-Eltze
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-06-18
Latest Update: 2019-09-20
Description:
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) , 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) .
How to cite:
Constantin Ahlmann-Eltze (2018). mixdir: Cluster High Dimensional Categorical Datasets. R package version 0.3.0, https://cran.r-project.org/web/packages/mixdir. Accessed 03 Jul. 2026.
Previous versions and publish date:
0.1.0 (2018-06-18 18:32), 0.2.0 (2019-03-11 21:40)
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Complete documentation for mixdir
Functions, R codes and Examples using the mixdir R package
Some associated functions: find_defining_features . find_predictive_features . find_typical_features . mixdir . mushroom . plot_features . predict.mixdir . 
Some associated R codes: RcppExports.R . data.R . mixdir.R . mixdir_vi.R . mixdir_vi_dp.R . predict.R .  Full mixdir package functions and examples
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