tCorpus-cash-lda_fit: Estimate a LDA topic model

Description Arguments Value Examples

Description

Estimate an LDA topic model using the LDA function from the topicmodels package. The parameters other than dtm are simply passed to the sampler but provide a workable default. See the description of that function for more information

Usage:

## R6 method for class tCorpus. Use as tc$method (where tc is a tCorpus object).

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lda_fit(feature, create_feature=NULL, K=50, num.iterations=500, alpha=50/K,
     eta=.01, burnin=250, context_level=c('document','sentence'), ...)

Arguments

feature

the name of the feature columns

create_feature

optionally, add a feature column that indicates the topic to which a feature was assigned (in the last iteration). Has to be a character string, that will be the name of the new feature column

K

the number of clusters

num.iterations

the number of iterations

method

set method. see documentation for LDA function of the topicmodels package

alpha

the alpha parameter

eta

the eta parameter#'

burnin

The number of burnin iterations

Value

A fitted LDA model, and optionally a new column in the tcorpus (added by reference)

Examples

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## Not run: 
tc = create_tcorpus(sotu_texts, doc_column = 'id')
tc$preprocess('token', 'feature', remove_stopwords = TRUE, use_stemming = TRUE, min_freq=10)
set.seed(1)
m = tc$lda_fit('feature', create_feature = 'lda', K = 5, alpha = 0.1)

m
topicmodels::terms(m, 10)
tc$get()

## End(Not run)

kasperwelbers/corpustools documentation built on Sept. 1, 2018, 1:03 p.m.