Classifier on top of LDA topic vectors?
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16-10-2019 - |
Question
I have training data in form of pair of documents with an associated label - {doc1, doc2, label}. Label is defined as function of pair of documents.
Now I want to build a model which can predict the label given two new documents.
I want to try different representation of document (instead of common ones say TF-IDF). Can I use vectors (topic distribution) from LDA as features for a classifier?
Solution
Yes, that is a reasonable approach. Also try neural network based representations such as doc2vec. I suppose you know how to do the classification part?
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