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Questions tagged [topicmodels]

topicmodels is an R package implementing Latent Dirichlet Allocation topic modeling.

Excerpt from topicmodels page on CRAN:

Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.

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LDA with topicmodels package for R, how do I get the topic probability for each term?

I'm using the topicmodels package for LDA. I would like to create a visualization that shows how related or non-related each topic is. I envision a cluster of words that are unique to topic 1, but with a few keywords that are shared connecting to…
lmcshane
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R in Windows cannot handle some characters

I performed LDA in Linux and didn't get characters like "ø" in topic 2. However, when run in Windows, they show. Does anyone know how to deal with this? I used packages quanteda and topicmodels. > terms(LDAModel1,5) Topic 1 Topic 2 [1,] "car" …
user1569341
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how to get a probability distribution for a topic in mallet?

Using mallet I can get a specific number of topics and their words. How can I make sure topic words make a probability distribution (ie sum to one)? For example if I run it as bellow, how can I use the outputs given by mallet to make sure…
samsamara
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Predicting topics with LDA

I am trying to extract topic assignments from a fit I build with R's 'lda' package. I created a fit: fit <- lda.collapsed.gibbs.sampler(documents = documents, K = K, vocab = vocab, num.iterations = G, alpha = alpha, eta = eta, initial = NULL, …
Sylvia
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DocumentTermMatrix() return 0 terms in tm package

I have an object like that: str(apps) chr [1:17517] "35 44 33 40 33 40 44 38 33 37 37" ... In each row, the number is separated by space. corpus<-Corpus(VectorSource(apps)) dtm<-DocumentTermMatrix(corpus) str(dtm) List of 6 $ i : int(0) $…
ysfseu
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Different results of LDA using R(topicmodels)

I am using R topicmodels to train an LDA model from a small corpus, but I find that every time I repeat the same code, it has the different results (different topics and different topic terms) My question is why the same condition and same corpus…
Snow
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Manually Specifying a Topic Model in R

I have a corpus of text with each line in the csv file uniquely specifying a "topic" I am interested in. If I were to run an topic model on this corpus using an LDA or Gibbs method from either the topicmodels package or lda, as expected I would get…
william
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which.max(sapply, train_gibbs, logLik) error

So, I am following Grun and Hornik (http://www.jstatsoft.org/v40/i13/) method of 10 fold cross validation by calculating perplexity from 10-fold training and test set. But I have error when I create test_gibbs which is stated the end of the code…
user37874
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document-topic probability after training topic models using "topicmodels" in R: gamma or posterior()?

Below is what I get after training 3328 text files using gibbs sampling. I need to save a file that contains document_topic probability. Is gamma the document-topic probability? But most of the numbers are smoothed and not very informative in terms…
user37874
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How do you normalize the rows of a document term matrix in place in R?

I have a DocumentTermMatrix named train_dtm and I want to normalize the frequency counts of the term frequencies in all the documents. The problem I am facing is that the resulting matrix should also be of type DocumentTermMatrix because I want to…
London guy
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R: topicmodels, 2 similar documents, code works with one, doesnt with the other

I have a quite strange error occuring when i run my topicmodel code. Basically I have a .csv file with user comments. I want to create a dtm with each comment being one document. i took a sample of 8k comments and used the following code on it: >…
Andres
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