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lda (version 1.1)

Collapsed Gibbs sampling methods for topic models.

Description

This package implements latent Dirichlet allocation (LDA) and related models. This includes (but is not limited to) sLDA, corrLDA, and the mixed-membership stochastic blockmodel. Inference for all of these models is implemented via a fast collapsed Gibbs sampler writtten in C. Utility functions for reading/writing data typically used in topic models, as well as tools for examining posterior distributions are also included.

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Version

Install

install.packages('lda')

Monthly Downloads

4,602

Version

1.1

License

LGPL

Maintainer

Jonathan Chang

Last Published

September 29th, 2009

Functions in lda (1.1)

lda-package

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

Generate LDA Documents from Raw Text
poliblog

A collection of political blogs with ratings.
cora

A subset of the Cora dataset of scientific documents.
word.counts

Compute Summary Statistics of a Corpus
predictive.link.probability

Use the RTM to predict whether a link exists between two documents.
sampson

Sampson monk data
links.as.edgelist

Convert a set of links keyed on source to a single list of edges.
top.topic.words

Get the Top Words and Documents in Each Topic
nubbi.collapsed.gibbs.sampler

Collapsed Gibbs Sampling for the Networks Uncovered By Bayesian Inference (NUBBI) Model.
filter.words

Functions to manipulate text corpora in LDA format.
predictive.distribution

Compute predictive distributions for fitted LDA-type models.
rtm.collapsed.gibbs.sampler

Collapsed Gibbs Sampling for the Relational Topic Model (RTM).
read.documents

Read LDA-formatted Document and Vocabulary Files
lda.collapsed.gibbs.sampler

Functions to Fit LDA-type models