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

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.

Version: 0.1.1
Depends: R (≥ 3.5.0)
Imports: skmeans, extraDistr, dplyr, Rfast, entropy, ggplot2, graphics, MASS
Published: 2021-03-04
Author: Martin D'Ippolito [aut, cre], Anderlucci Laura [aut], Cinzia Viroli [aut]
Maintainer: Martin D'Ippolito <martinmy69 at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: deepMOU results

Documentation:

Reference manual: deepMOU.pdf

Downloads:

Package source: deepMOU_0.1.1.tar.gz
Windows binaries: r-devel: deepMOU_0.1.1.zip, r-release: deepMOU_0.1.1.zip, r-oldrel: deepMOU_0.1.1.zip
macOS binaries: r-release (arm64): deepMOU_0.1.1.tgz, r-oldrel (arm64): deepMOU_0.1.1.tgz, r-release (x86_64): deepMOU_0.1.1.tgz
Old sources: deepMOU archive

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