# What is "class" in mutual information based feature selection?

I'm having a little hard time understanding this specific feature selection algorithm.

Specifically, I am looking into maximum-relevance-minimum-redundancy method for feature selection.

If I have a feature matrix $\ X = \{x_1, x_2, ... , x_n\} , x_i \in R^D$

then I can compute mutual information between two specific individual features, but when talking about

relevance of that specific feature to a "class", in terms of mRMR algorithm,

what is exactly the definition of "class" ?

• If you look at Tom Cover's Information Theory book the result will be clear. Mar 8 '17 at 0:40