Classification of ADHD with fMRI data and multi-objective optimization.

•A novel multi-objective optimization classification scheme is proposed.•The scheme uses a cost sensitive three objective model to handle the class imbalance problem.•A preferred subset of pareto optimal classifiers can be obtained based on the decision maker's preference.•Results show that the proposed scheme performs considerably better than some traditional methods.