Multi-Classifier Systems: Review and a roadmap for developers

摘要: Multi-Classifier Systems (MCSs) have fast been gaining popularity among researchers for their ability to fuse together multiple classification outputs better accuracy and classification. At present, there is a lot of literature covering many the issues concerns that MCS designers encounters. However, we found out isn't single paper published thus far which presents an overall picture basic principles behind design multi-classifier systems. Therefore, this current overview MCSs provides road-map designers. We identify all key decisions designer would make over list most useful options available at each decision making step. also present case-study theoretical considered, informal guidelines selection different paradigms, based on properties distribution data. introduce novel optimization standard majority voting combiner uses genetic algorithm.