R: Collapsed Gibbs Samplers and Related Utility Functions for...

lda-package {lda} | R Documentation

## Collapsed Gibbs Samplers and Related Utility Functions for LDA-type Models

### Description

This package contains functions to read in text corpora, fit LDA-type models to them, and use the fitted models to explore the data and make predictions.

### Details

Package: | lda
Type: | Package
Version: | 1.3.2
Date: | 2012-05-22
License: | BSD
LazyLoad: | yes

### Author(s)

Jonathan Chang (slycoder@gmail.com) Andrew Dai (a.dai@ed.ac.uk)

Special thanks to the following for their reports and comments: Edo Airoldi, Jordan Boyd-Graber, Christopher E. Cramer, James Danowski, Khalid El-Arini, Roger Levy, Solomon Messing, Joerg Reichardt

### References

Blei, David M. and Ng, Andrew and Jordan, Michael. Latent Dirichlet allocation. Journal of Machine Learning Research, 2003.

### See Also

Functions to fit models: `lda.collapsed.gibbs.sampler` `slda.em` `mmsb.collapsed.gibbs.sampler` `nubbi.collapsed.gibbs.sampler` `rtm.collapsed.gibbs.sampler`

Functions to read/create corpora: `lexicalize` `read.documents` `read.vocab`

Functions to manipulate corpora: `concatenate.documents` `filter.words` `shift.word.indices` `links.as.edgelist`

Functions to compute summary statistics on corpora: `word.counts` `document.lengths`

Functions which use the output of fitted models: `predictive.distribution` `top.topic.words` `top.topic.documents` `predictive.link.probability`

Included data sets: `cora` `poliblog` `sampson`

### Examples

    ## See demos for the following three common use cases:

    ## Not run: demo(lda)

    ## Not run: demo(slda)

    ## Not run: demo(mmsb)

    ## Not run: demo(rtm)

[Package lda version 1.4.2 Index]