Binary semi-supervised classification with positive only and unlabeled data set

Question

My data consist of comments (saved in files) and few of them are labelled as positive. I would like to use semi-supervised and PU classification to classify these comments i

Answer 1

You could try to train a one-class SVM and see what kind of results that gives you. I haven't heard about the PU paper. I think for all practical purposes you will be much better of labelling some points and then using semi-supervised methods. If finding negative points is hard, I would try to use heuristics to find putative negative points (which I think is similar to the techniques in the PU paper). You could either classify unlabelled vs positive and then only look at the ones that score strongly for unlabelled, or learn a one-class SVM or similar and then look for negative points in the outliers.

If you are interested in actually solving the task, I would much rather invest time in manual labelling than implementing fancy methods.