What are the key parameters to tune in LDA for topic modeling?
An example of an AI chatbot conversation about LDA parameters in Python machine learning.
What are the key parameters to tune in LDA for topic modeling?
The key parameters to tune in LDA include the number of topics, alpha, beta, and the number of iterations.
How do I choose the right number of topics?
You can use methods like coherence score or perplexity to evaluate different numbers of topics.
What is the role of alpha and beta in LDA?
Alpha controls the document-topic distribution, while beta controls the topic-word distribution.
Can you give an example of how to set these parameters in Python?
Sure! In Python, you can set these parameters using the gensim library when creating your LDA model.
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