# What model to use: Feature importance at each rank

My dataset contain a set of ordinal features and a rank from 1 to 10 which I'm trying to predict.

I'm looking for a way to understand which feature is most important at each rank.

Which model is best to use to get this information?

Would learning-to-rank models (RankSVM ...) work in this case? I'm not dealing with queries in this case.

If you are using sklearn then you can use a one-vs-rest strategy where you train one classifier for each "label" which in this case would be 10 classifiers, one for each rank. Every sample is then evaluated against each classifier and is assigned the label that gets the highest probability.