I'm attempting to classify text documents using a few different dimensions. I'm trying to create arbitrary topics to classify such as size and relevance, which are linear or gradual in nature. For example:
size: tiny, small, medium, large, huge. relevance: bad, ok, good, excellent, awesome
I am training the classifier by hand. For example, this document represents a 'small' thing, this other document is discussing a 'large' thing. When I try multi-label or multi-class SVM for this it does not work well and it also logically doesn't make sense.
Which model should I use that would help me predict this linear type of data? I use scikit-learn presently with a tfidf vector of the words.