A NOVEL ALGORITHM FOR FINDING ALL REDUCTS IN THE INCOMPLETE DECISION TABLE

Attribute reduction, or attribute selection in the decision table, is a fundamental problem of rough set theory. Currently, many scientists are interested in and developing these issues. Unfortunately, most studies focus mainly on the complete decision table. On incomplete decision tables, researchers have proposed tolerance relations and designed attribute reduction algorithms based on different measures. However, these algorithms only return a reduct and do not preserve information in the decision tables. This paper will propose an efficient method to determine entire reducts of incomplete decision tables according to the relational database approach. In the complex case, this algorithm has exponential computational complexity. However, this algorithm has polynomial computational complexity in the different cases of databases.