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## Package cc.mallet.topics

Class Summary
DMROptimizable |
DMRTopicModel |
HierarchicalLDA |
HierarchicalPAM | Hierarchical PAM, where each node in the DAG has a distribution over all topics on the next level and one additional "node-specific" topic.
LDA | Deprecated. Use ParallelTopicModel instead.
LDAHyper | Deprecated. Use ParallelTopicModel instead, which uses substantially faster data structures even for non-parallel operation.
LDAStream |
MarginalProbEstimator | An implementation of topic model marginal probability estimators presented in Wallach et al., "Evaluation Methods for Topic Models", ICML (2009)
MultinomialHMM | Latent Dirichlet Allocation.
NPTopicModel | A non-parametric topic model that uses the "minimal path" assumption to reduce bookkeeping.
PAM4L | Four Level Pachinko Allocation with MLE learning, based on Andrew's Latent Dirichlet Allocation.
ParallelTopicModel | Simple parallel threaded implementation of LDA, following the UCI NIPS paper, with SparseLDA sampling scheme and data structure.
PolylingualTopicModel | Latent Dirichlet Allocation for loosely parallel corpora in arbitrary languages
SimpleLDA | A simple implementation of Latent Dirichlet Allocation using Gibbs sampling.
TopicalNGrams | Like Latent Dirichlet Allocation, but with integrated phrase discovery.
TopicAssignment | This class combines a sequence of observed features with a sequence of hidden "labels".
TopicInferencer |
WorkerRunnable | A parallel topic model runnable task.

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