LDA Topic assignment

Question

I have a corpora of ~1,400 documents. I did all text cleansing using tm package. My last step was creation of the DTM matrix. I am trying to train the LDA model based on 200 documents examined by human and topics(categories) that were assigned. Unfortunately, I can't share the reproducible example.

Can someone help how is this performed with one of the freely available data sets as an example?

Answer 1

If you have annotated training data, why don't you use supervised classification techniques like SVM or logistic regression which are pretty good for text classification tasks. Scikit-learn in python has all the implementation for these classifiers and you can directly use them for the classification purpose.