A new rough set approach to knowledge discovery in incomplete information systems

The purpose of this paper is to deal with knowledge acquisition in incomplete decision tables. The concept of labeled block set in incomplete information systems is proposed. Two kinds of partitions, lower and upper approximations, are then formed for the mining of certain and possible rules in incomplete decision tables. The induction of optimal rules in such tables is also examined.