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 |