lda: Collapsed Gibbs sampling methods for topic models This package implements latent Dirichlet allocation (LDA) and related models. This includes (but is not limited to) sLDA, corrLDA, and the mixed-membership stochastic blockmodel. Inference for all of these models is implemented via a fast collapsed Gibbs sampler writtten in C. Utility functions for reading/writing data typically used in topic models, as well as tools for examining posterior distributions are also included.

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References in zbMATH (referenced in 2 articles )

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  1. Williamson, Sinead A.: Nonparametric network models for link prediction (2016)
  2. Zhao, Yanchang: R and data mining. Examples and case studies (2013)