Algorithm for generating rules for classifying documents Im looking for an algorithm that can deduct a set of rules based on a dataset of "training documents" that can be applied to classify a new unseen document. The problem is that I need these rules to be viewable by the user in the form of some string representation. For example, the algorithm found that documents have a minimum word count of 1000 and that there are 4 citations in each document. The key is that these rules must be deducted by a algorithm. An example of this in practice would be:  

Document 1 contains 890 words and only 2 citations

I need it to return something like:  

- You should add more words to make it better
- Add more citations to prove your point
I think a simplest way is like this: convert the document to a vector like "bag of words" or "n-grams", then apply algorithm which can be used to derive rules Decision tree or LEM2.