Integer programming models for feature selection: New extensions and a randomized solution algorithm
Feature Selection (FS) is modelled as a (mixed) integer optimization problem. To solve this problem, a new FS algorithm (FSA) with short memory is proposed. This algorithm has been already successfully applied to life science data. New experiments on randomly generated and real biological datasets are reported. The results are compared w.r.t. other FSA confirming the validity of our approach.
integer programming data mining heuristics