plot_perplexity: Plot perplexity score of various LDA models

In JulFriedrich/miRetrieve: miRNA Text Mining in Abstracts

Description

Plot perplexity score of various LDA models.

Usage

plot_perplexity(
  df,
  start = 2,
  end = 5,
  stopwords = stopwords_miretrieve,
  method = "gibbs",
  control = NULL,
  col.abstract = Abstract,
  col.pmid = PMID,
  title = NULL
)

Arguments

df	Data frame containing abstracts and PubMed-IDs.
start	Integer. Minimum amount of k topics for the LDA model to fit. Must be >=2.
end	Integer. Maximum amount of k topics for the LDA model to fit.
stopwords	Data frame containing stop words.
method	String. Either "gibbs" or "VEM".
control	Control parameters for LDA modeling. For more information, see the documentation of the LDAcontrol class in the topicmodels package.
col.abstract	Column containing abstracts.
col.pmid	Column containing PubMed-ID.
title	String. Plot title.

Details

Plot perplexity score of various LDA models. plot_perplexity() fits different LDA models for k topics in the range between start and end. For each LDA model, the perplexity score is plotted against the corresponding value of k. Plotting the perplexity score of various LDA models can help in identifying the optimal number of topics to fit an LDA model for. plot_perplexity() is based on LDA() from the package topicmodels.

Value

Elbow plot displaying perplexity scores of different LDA models.

See Also

fit_lda()

Other LDA functions: assign_topic_lda(), fit_lda(), plot_lda_term()

JulFriedrich/miRetrieve documentation built on Sept. 20, 2021, 11:37 p.m.