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Questions - topic-modeling

How can I find the optimal number of topics in LDA with scikit-learn?

I'm computing topic models through scikit-learn with this script (I'm starting with a dataset "df" which has one document per row in the column "Text") from sklearn.decomposition i...
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Himan

optimization

scikit-learn

lda

topic-modeling

hyperparameters

Votes: 0

Answers: 0

Topic modelling- Calculate the coherence score of an sklearn LDA model?

I tried several things to calculate the coherence score for a sklearn LDA model, but it does not work out. What is a way to calculate the Coherence score for a sklearn LDA model? When I use the standa...
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Selena

python

scikit-learn

nlp

lda

topic-modeling

Votes: 0

Answers: 1

Latest Answer

I think you can use this code below for coherence model in LDA: # import library from gensim from gensim.models import CoherenceModel # instantiate topic coherence model cm = CoherenceModel(model=l...
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Hansen Idden

Topic Modelling: WordCloud For Every Topic in LDA model

Question: How can I create a Word Cloud for each topic that has been computed by the LDA model. I tried the following, but can't seem to work it out further to create a word cloud for each topic. firs...
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Selena

python

nlp

lda

topic-modeling

word-cloud

Votes: 0

Answers: 1

Latest Answer

you can try this: def create_wordcloud(model, topic): text = {word: value for word, value in model.show_topic(topic)} wc = WordCloud(background_color="white", max_words=1000) wc....
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hajar hajar

Error in .rect_dendrogram(dend, k = k, palette = rect_border, rect_fill = rect_fill, : k must be between 2 and 97

I am trying to estimate a cluster dendrogram in R for a structural topic model I produced with 98 topics. I first ran the following which worked well: res.hc <- eclust(scale(out_corr$cor), "hc...
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md_14

r

hierarchical-clustering

topic-modeling

dendrogram

dendextend

Votes: 0

Answers: 1

Latest Answer

The following steps helped to resolve the issue: estimate cluster dendrogram res.hc <- eclust(scale(out_corr$cor), "hclust", nboot = 500) install dendextend install.packages("de...
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md_14

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