lda_fgs_perplexity: LDA: Full Gibbs Sampler with Perplexity Computation

In clintpgeorge/ldamcmc: Markov chain Monte Carlo Algorithms for the Latent Dirichlet Allocation Model

Description

Implements the Full Gibbs sampler for the LDA model—a Markov chain on (β, θ, z). To compute perplexity, it first partitions each document in the corpus into two sets of words: (a) a test set (held-out set) and (b) a training set, given a user defined test_set_share. Then, it runs the Markov chain based on the training set and computes perplexity for the held-out set.

Usage

lda_fgs_perplexity(num_topics, vocab_size, docs_tf, alpha_h, eta_h, max_iter,
  burn_in, spacing, save_theta, save_beta, save_lp, verbose, test_set_share)

Arguments

num_topics	Number of topics in the corpus
vocab_size	Vocabulary size
docs_tf	A list of corpus documents read from the Blei corpus using read_docs (term indices starts with 0)
alpha_h	Hyperparameter for θ sampling
eta_h	Smoothing parameter for the β matrix
max_iter	Maximum number of Gibbs iterations to be performed
burn_in	Burn-in-period for the Gibbs sampler
spacing	Spacing between the stored samples (to reduce correlation)
save_theta	if 0 the function does not save θ samples
save_beta	if 0 the function does not save β samples
save_lp	if 0 the function does not save computed log posterior for iterations
verbose	from 0, 1, 2
test_set_share	proportion of the test words in each document. Must be between 0. and 1.

Value

The Markov chain output as a list of

corpus_topic_counts	corpus-level topic counts from last iteration of the Markov chain
theta_counts	document-level topic counts from last iteration of the Markov chain
beta_counts	topic word counts from last iteration of the Markov chain
theta_samples	θ samples after the burn in period, if save_theta is set
beta_samples	β samples after the burn in period, if save_beta is set
log_posterior	the log posterior (upto a constant multiplier) of the hidden variable ψ = (β, θ, z) in the LDA model, if save_lp is set
perplexity	perplexity of the held-out words' set

See Also

Other MCMC: lda_acgs_st, lda_cgs_em_perplexity, lda_cgs_em, lda_cgs_perplexity, lda_fgs_BF_perplexity, lda_fgs_ppc, lda_fgs_st_perplexity

clintpgeorge/ldamcmc documentation built on Feb. 22, 2020, 12:39 p.m.