lda-package |
Collapsed Gibbs Sampling Methods for Topic Models |
concatenate.documents |
Functions to manipulate text corpora in LDA format. |
cora |
A subset of the Cora dataset of scientific documents. |
cora.cites |
A subset of the Cora dataset of scientific documents. |
cora.documents |
A subset of the Cora dataset of scientific documents. |
cora.titles |
A subset of the Cora dataset of scientific documents. |
cora.vocab |
A subset of the Cora dataset of scientific documents. |
document.lengths |
Compute Summary Statistics of a Corpus |
filter.words |
Functions to manipulate text corpora in LDA format. |
lda |
Collapsed Gibbs Sampling Methods for Topic Models |
lda.collapsed.gibbs.sampler |
Functions to Fit LDA-type models |
lda.cvb0 |
Functions to Fit LDA-type models |
lexicalize |
Generate LDA Documents from Raw Text |
links.as.edgelist |
Convert a set of links keyed on source to a single list of edges. |
mmsb.collapsed.gibbs.sampler |
Functions to Fit LDA-type models |
newsgroup |
A collection of newsgroup messages with classes. |
newsgroup.label.map |
A collection of newsgroup messages with classes. |
newsgroup.test.documents |
A collection of newsgroup messages with classes. |
newsgroup.test.labels |
A collection of newsgroup messages with classes. |
newsgroup.train.documents |
A collection of newsgroup messages with classes. |
newsgroup.train.labels |
A collection of newsgroup messages with classes. |
newsgroup.vocab |
A collection of newsgroup messages with classes. |
nubbi.collapsed.gibbs.sampler |
Collapsed Gibbs Sampling for the Networks Uncovered By Bayesian Inference (NUBBI) Model. |
poliblog |
A collection of political blogs with ratings. |
poliblog.documents |
A collection of political blogs with ratings. |
poliblog.ratings |
A collection of political blogs with ratings. |
poliblog.vocab |
A collection of political blogs with ratings. |
predictive.distribution |
Compute predictive distributions for fitted LDA-type models. |
predictive.link.probability |
Use the RTM to predict whether a link exists between two documents. |
read.documents |
Read LDA-formatted Document and Vocabulary Files |
read.vocab |
Read LDA-formatted Document and Vocabulary Files |
rtm.collapsed.gibbs.sampler |
Collapsed Gibbs Sampling for the Relational Topic Model (RTM). |
rtm.em |
Collapsed Gibbs Sampling for the Relational Topic Model (RTM). |
sampson |
Sampson monk data |
shift.word.indices |
Functions to manipulate text corpora in LDA format. |
slda.em |
Functions to Fit LDA-type models |
slda.predict |
Predict the response variable of documents using an sLDA model. |
slda.predict.docsums |
Predict the response variable of documents using an sLDA model. |
top.topic.documents |
Get the Top Words and Documents in Each Topic |
top.topic.words |
Get the Top Words and Documents in Each Topic |
word.counts |
Compute Summary Statistics of a Corpus |