|¡¡||Chinese Journal of Computers Full Text|
|Title||Decision table reduction based on conditional information entropy|
|Authors||WANG Guo-yin/YU Hong1/YANG Da-chun|
| Abstract &|
|This paper analyzes the information view of rough set theory and compares it with the algebra view of rough set theory. Some equivalence relations and other kind of relations like inclusion relation between the information view and the algebra view of rough set theory are resulted through comparing each other. Two novel heuristic knowledge reduction algorithms are developed based on conditional information entropy, that is, conditional entropy based algorithm for reduction of knowledge with computing core (CEBARKCC) and conditional entropy based algorithm for reduction of knowledge without computing core (CEBARKNC). These two algorithms are compared with a mutual information based algorithm for reduction of knowledge (MIBARK) of Duoqian Miao through theoretical analysis and experimental simulation. CEBARKCC algorithm and CEBARKNC algorithm have good performance in simulation.
keywords Rough sets, Information entropy, Approximate set, Equivalence, Knowledge reduction