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deepMOU

Clustering of Short Texts by Mixture of Unigrams and Its Deep Extensions

v0.1.1 · Mar 3, 2021 · GPL-3

Description

Functions providing an easy and intuitive way for fitting and clusters data using the Mixture of Unigrams models by means the Expectation-Maximization algorithm (Nigam, K. et al. (2000). <doi:10.1023/A:1007692713085>), Mixture of Dirichlet-Multinomials estimated by Gradient Descent (Anderlucci, Viroli (2020) <doi:10.1007/s11634-020-00399-3>) and Deep Mixture of Multinomials whose estimates are obtained with Gibbs sampling scheme (Viroli, Anderlucci (2020) <doi:10.1007/s11222-020-09989-9>). There are also functions for graphical representation of clusters obtained.

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dependencies in R code

Namespace in Imports field not imported from: ‘dplyr’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespace in Imports field not imported from: ‘dplyr’
  All declared Imports should be used.
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Check History

NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-fedora-clang

dependencies in R code

Namespace in Imports field not imported from: ‘dplyr’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespace in Imports field not imported from: ‘dplyr’
  All declared Imports should be used.

Dependency Network

Dependencies Reverse dependencies skmeans extraDistr dplyr Rfast entropy ggplot2 MASS deepMOU

Version History

new 0.1.1 Mar 9, 2026