CalcGamma |
Calculate a matrix whose rows represent P(topic_i|tokens) |
CalcHellingerDist |
Calculate Hellinger Distance |
CalcJSDivergence |
Calculate Jensen-Shannon Divergence |
CalcLikelihood |
Calculate the log likelihood of a document term matrix given a topic model |
CalcLikelihoodC |
Internal helper functions for 'textmineR' |
CalcProbCoherence |
Probabilistic coherence of topics |
CalcSumSquares |
Internal helper functions for 'textmineR' |
CalcTopicModelR2 |
Calculate the R-squared of a topic model. |
Cluster2TopicModel |
Represent a document clustering as a topic model |
CreateDtm |
Convert a character vector to a document term matrix. |
CreateTcm |
Convert a character vector to a term co-occurrence matrix. |
Dtm2Docs |
Convert a DTM to a Character Vector of documents |
Dtm2DocsC |
Internal helper functions for 'textmineR' |
Dtm2Lexicon |
Turn a document term matrix into a list for LDA Gibbs sampling |
Dtm2Tcm |
Turn a document term matrix into a term co-occurrence matrix |
dtm_to_lexicon_c |
Internal helper functions for 'textmineR' |
FitCtmModel |
Fit a Correlated Topic Model |
FitLdaModel |
Fit a Latent Dirichlet Allocation topic model |
FitLsaModel |
Fit a topic model using Latent Semantic Analysis |
fit_lda_c |
Internal helper functions for 'textmineR' |
GetProbableTerms |
Get cluster labels using a "more probable" method of terms |
GetTopTerms |
Get Top Terms for each topic from a topic model |
HellingerMat |
Internal helper functions for 'textmineR' |
Hellinger_cpp |
Internal helper functions for 'textmineR' |
JSDmat |
Internal helper functions for 'textmineR' |
JSD_cpp |
Internal helper functions for 'textmineR' |
LabelTopics |
Get some topic labels using a "more probable" method of terms |
nih |
Abstracts and metadata from NIH research grants awarded in 2014 |
nih_sample |
Abstracts and metadata from NIH research grants awarded in 2014 |
nih_sample_dtm |
Abstracts and metadata from NIH research grants awarded in 2014 |
nih_sample_topic_model |
Abstracts and metadata from NIH research grants awarded in 2014 |
posterior |
Posterior methods for topic models |
posterior.lda_topic_model |
Draw from the posterior of an LDA topic model |
predict.ctm_topic_model |
Predict method for Correlated topic models (CTM) |
predict.lda_topic_model |
Get predictions from a Latent Dirichlet Allocation model |
predict.lsa_topic_model |
Predict method for LSA topic models |
predict_lda_c |
Internal helper functions for 'textmineR' |
SummarizeTopics |
Summarize topics in a topic model |
TermDocFreq |
Get term frequencies and document frequencies from a document term matrix. |
textmineR |
textmineR |
TmParallelApply |
An OS-independent parallel version of 'lapply' |
update |
Update methods for topic models |
update.lda_topic_model |
Update a Latent Dirichlet Allocation topic model with new data |