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Incremental Learning Researches on Rough Set Theory: Status and Future

Rough set theory is an effective tool to deal with information with uncertainty, and has been successfully applied in many fields. Incremental learning as an efficient strategy for data analysis in dynamic environment enables acquiring additional knowledge from new information by using prior knowledge and has drawn the widespread attentions of many scholars. In this paper, the authors discuss the status of incremental learning researches on rough sets and give potential future research directions. The authors first review basic concepts of rough sets and list three variations of information system in the dynamic decision procedures. Then, the authors investigate and summarize the corresponding incremental learning strategies for the three variations with different research viewpoints, respectively. Finally, the authors further tease out the research framework of our work and identify some future possible research directions.