MoMPCA: MoMPCA: Greedy clustering of count data through a mixture of...
In nicolasJouvin/MoMPCA: Inference and Clustering for Mixture of Multinomial Principal Component Analysis
Description
The MMPCA package implements the branch & bound classification-Variational
Expectation Maximisation algorithm described in Jouvin et. al.
https://arxiv.org/abs/1909.00721. It enables the clustering of counts
data such as document/term matrix modeled as a mixture of multinomial PCA
model. Model selection is performed via an approximated form of the
Integrated Classification Likelihood. .
Details
The main entry point is the mmpca_clust() function to perfom
the clustering.
nicolasJouvin/MoMPCA documentation built on Jan. 24, 2021, 11:23 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
The MMPCA package implements the branch & bound classification-Variational Expectation Maximisation algorithm described in Jouvin et. al. https://arxiv.org/abs/1909.00721. It enables the clustering of counts data such as document/term matrix modeled as a mixture of multinomial PCA model. Model selection is performed via an approximated form of the Integrated Classification Likelihood. .
Details
The main entry point is the mmpca_clust() function to perfom
the clustering.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.