Description Usage Arguments Value References Examples
View source: R/topic_diagnostics.R
Generate a dataframe containing the diagnostics for each topic in a topic model
1 2 3  topic_diagnostics(topic_model, dtm_data, top_n_tokens = 10,
method = c("gamma_threshold", "largest_gamma"),
gamma_threshold = 0.2)

topic_model 
a fitted topic model object from one of the following:

dtm_data 
a documentterm matrix of token counts coercible to 
top_n_tokens 
an integer indicating the number of top words to consider for mean token length 
method 
a string indicating which method to use  "gamma_threshold" or "largest_gamma" 
gamma_threshold 
a number between 0 and 1 indicating the gamma threshold to be used when using the gamma threshold method, the default is 0.2 
A dataframe where each row is a topic and each column contains the associated diagnostic values
Jordan BoydGraber, David Mimno, and David Newman, 2014. Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements. CRC Handbooks ofModern Statistical Methods. CRC Press, Boca Raton, Florida.
1 2 3 4 5  # Using the example from the LDA function
library(topicmodels)
data("AssociatedPress", package = "topicmodels")
lda < LDA(AssociatedPress[1:20,], control = list(alpha = 0.1), k = 2)
topic_diagnostics(lda, AssociatedPress[1:20,])

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