Package org.apache.mahout.clustering.lda

Class Summary
LDADocumentTopicMapper  
LDADriver Estimates an LDA model from a corpus of documents, which are SparseVectors of word counts.
LDAInference Class for performing infererence on a document, which involves computing (an approximation to) p(word|topic) for each word and topic, and a prior distribution p(topic) for each topic.
LDAInference.InferredDocument An estimate of the probabilities for each document.
LDAReducer A very simple reducer which simply logSums the input doubles and outputs a new double for sufficient statistics, and sums log likelihoods.
LDASampler Takes in a Matrix of topic distributions (such as generated by LDADriver, CVB0Driver or InMemoryCollapsedVariationalBayes0, and constructs a set of samplers over this distribution, which may be sampled from by providing a distribution over topics, and a number of samples desired
LDAState  
LDAWordTopicMapper Runs inference on the input documents (which are sparse vectors of word counts) and outputs the sufficient statistics for the word-topic assignments.
 



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