An incremental rough set approach for faster attribute reduction

Effective Attribute Reduction Algorithm Based on Fuzzy Uncertainties Using Shared Neighborhood Granulation

“…I N 1982, Professor Z. Pawlak coined the rough set theory which is generally acknowledged as an efficient and relatively new mathematical implement to process the incomplete, inaccurate, and undefinable data [1]- [3]. In rough set theory, no extra information is needed, thus it has gained huge attention from considerable number of researchers across a lot of fields, to name a few, artificial intelligence, decision making, machine learning, granular computing, data mining [4]- [6].…”