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| 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' |
| CalcPhiPrime | Calculate a matrix whose rows represent P(topic_i|tokens) |
| CalcProbCoherence | Probailistic 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 |
| CorrectS | Function to remove some forms of pluralization. |
| CreateDtm | Convert a character vector to a document term matrix. |
| CreateTcm | Convert a character vector to a term co-occurence matrix. |
| DepluralizeDtm | Run the CorrectS function on columns of a document term matrix. |
| Dtm2Docs | Convert a DTM to a Character Vector of documents |
| Dtm2DocsC | Internal helper functions for 'textmineR' |
| Dtm2Tcm | Turn a document term matrix into a term co-occurence matrix |
| Files2Vec | Function for reading text files into R |
| FitCtmModel | Fit a Correlated Topic Model |
| FitLdaModel | Fit a topic model using Latent Dirichlet Allocation |
| FitLsaModel | Fit a topic model using Latent Semantic Analysis |
| FormatRawLdaOutput | Format Raw Output from 'lda.collapsed.gibbs.sampler' |
| GetPhiPrime | Calculate a matrix whose rows represent P(topic_i|tokens) |
| GetProbableTerms | Get cluster labels using a "more probable" method of terms |
| GetTopTerms | Get Top Terms for each topic from a topic model |
| GetVocabFromDtm | Reconstruct a 'text2vec::vocabulary' object from a document term matrix. |
| HellDist | Hellinger Distance |
| HellingerMat | Internal helper functions for 'textmineR' |
| Hellinger_cpp | Internal helper functions for 'textmineR' |
| JSD | Jensen-Shannon Divergence |
| 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 |
| RecursiveRbind | Recursively call rBind from the Matrix package. |
| TermDocFreq | Get term frequencies and document frequencies from a document term matrix. |
| TmParallelApply | An OS-independent parallel version of 'lapply' |
| Vec2Dtm | Convert a character vector to a document term matrix of class Matrix. |