Using rough sets for rough classification
Jianhua Shao · 2002
Rough sets theory is emerging as a powerful tool for knowledge discovery in databases. The author introduce a rough sets based method for learning classification rules. The author's method will not necessarily derive all the consistent classification rules from a database, nor will the rules derived be totally consistent with the database. Rules are derived when they meet some user specified criteria. The author argues that the method is more useful in dealing with noisy data, and in deriving simpler classification rules.