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LDA model estimation

Source: R/lda_models.R
perform_lda.Rd

perform_lda() estimates a Latent Dirichlet Allocation (LDA) model on the counts matrix of a tidytacos object. The function returns the estimated topics and terms, as well as the perplexity of the model.

Usage

perform_lda(
  ta,
  k,
  min_prevalence = 0.05,
  taxon = taxon_id,
  sample = sample_id,
  ...
)

Arguments

ta

A tidytacos object.

k

The number of topics to estimate.

min_prevalence

The lowest percentage (0-1) of samples taxa need to be present in for the taxa to be used in model estimation.

taxon

The column name in the taxa table with taxa identifiers.

sample

The column name in the sample table with sample identifiers.

...

Arguments passed on to topicmodels::LDA

x

Object of class "DocumentTermMatrix" with term-frequency weighting or an object coercible to a "simple_triplet_matrix" with integer entries.

method

The method to be used for fitting; currently method = "VEM" or method= "Gibbs" are supported.

control

A named list of the control parameters for estimation or an object of class "LDAcontrol".

model

Object of class "LDA" for initialization.

Value

A list of estimated topics, terms and the perplexity of the model.