Does anyone have experience with using Cosine Similarity for text classification? I see a number of articles on how to find cosine similarity between documents using Doc2Vec, Gensim, etc.
I have a classification problem (binary) where I want to try out the cosine similarity. I do know how to calculate it, but all the articles that I see only explain until the point of calculating it between two documents.
Right now, I am planning to do this.
Calculate the cosine similarity of 'my paragraph' (the one that I want to classify) with all samples in
classi(their class is known). Then take the average (call that
Calculate the cosine similarity of my paragraph (the one that I want to classify) with all samples in
classo(their class is known). Then take the average (call that
avgoand then predict the class for 'my paragraph'
That sounds like a very manual way of doing it. Is there some better/widely used way of doing it?