scikit-learn classification using doc2vec representation

Question

I want to classify text documents using doc2vec representation and scikit-learn models.

My problem is that I'm lost on how to get started. can someone explain the general steps usually taken to use doc2vec with scikit-learn?

Answer 1

There is a great tutorial here for a binary classification with scikit-learn + doc2vec. In short:

• Using gensim to train/load your doc2vec model.
• Input text will be converted to a fixed dimension vector of floats (the same dimension as your embedding). These are the actual input features.
• Now feel free to use any classifier in scikit-learn.