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deepMOU (version 0.1.1)

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

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). ), Mixture of Dirichlet-Multinomials estimated by Gradient Descent (Anderlucci, Viroli (2020) ) and Deep Mixture of Multinomials whose estimates are obtained with Gibbs sampling scheme (Viroli, Anderlucci (2020) ). There are also functions for graphical representation of clusters obtained.

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Version

Install

install.packages('deepMOU')

Monthly Downloads

230

Version

0.1.1

License

GPL-3

Maintainer

Martin D'Ippolito

Last Published

March 4th, 2021

Functions in deepMOU (0.1.1)

words_freq_plot

Graph of most frequent words of each cluster
dir_mult_GD

Dirichlet-Multinomial mixture model by Gradient Descend algorithm
CNAE2

CNAE dataset on classes 4 and 9
mou_EM

Mixture of Unigrams by Expectation-Maximization algorithm
bubble_clust

Bubble plot
cl_CNAE

Classification labels of the CNAE2 data set
heatmap_words

Heatmap of word frequencies by cluster
plot.deepMOU

Plotting method for "shallow" and deep mixtures of Unigrams and mixtures of Dirichlet-Multinomials
deep_mou_gibbs

Deep Mixture of Unigrams
Abstracts

Abstracts dataset