Name
Abstract | ||
|---|---|---|
Rough Rough set-based decision rule extraction is a useful tool for data mining, however, almost approaches of decision rule extraction are based on comparison between values of the same attribute. On the other hand, the authors have proposed a concept of interrelationship mining that enables us to extract characteristics based on comparison between values of different attributes. In this paper, we consider logical aspects of interrelationship mining by introducing decision logic for interrelationship mining. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/GrC.2013.6740402 | Granular Computing |
Keywords | Field | DocType |
data mining,formal logic,rough set theory,data mining,decision logic,decision rule extraction,interrelationship mining,rough rough set,decision logic,interrelationship mining,low and high order decision rules,rough set | Decision rule,Decision table,Pattern recognition,Computer science,Rough set,Artificial intelligence,Machine learning,Decision tree learning,Dominance-based rough set approach | Conference |
Citations | PageRank | References |
2 | 0.39 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yasuo Kudo | 1 | 95 | 26.41 |
| Tetsuya Murai | 2 | 186 | 42.10 |