Topic Models
Extract most likely terms or topics.
Correlated Topic Model
Associated Press data
Compute Hellinger distance
Latent Dirichlet Allocation
Transform data from and for use with the lda package
Methods for Function logLik
Methods for Function perplexity
Determine posterior probabilities
Virtual class "TopicModel"
Different classes for controlling the estimation of topic models
Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.