Combining binary features with textual ones I have a binary feature that i want to use it with textual features i.e. unigrams. I use logistic regression and TF/IDF for representing text. So i simply add a unique feature, say ss or oo, to text of each instances. But in practice, i see adding more number of these features to instances, say two oo or ss or more get me a better results. What is the reason? How these weights improve the classification results? Should not logistic regression can get more weights to this features instead of weighting them by hand?
hstak is a good solution. Using this I combined these features.