Hi! So I’m building a classifier which primarily looks at text, but I also want to include other features, which are non-text, and I was wondering what is the best way to do it? I feel like just adding another dimension in the vector which represents the text might cause these features to get ‘lost’, but maybe that’s not true. Is ther there some sort of agreed upon way of including these additional non-text features in? By non-text I mean just information which is not part of the body of the text, like some other meta data.

Thanks!