Name
Abstract | ||
|---|---|---|
Attribute reduction is one of the basic contents in decision table. And it has been proved that computing the optimal attribute reduction is NP-complete. A lot of algorithms for the optimal attribute reduction were proposed in consistent decision table. But most decision tables are inconsistent in fact. In this paper, the judgment theorem with respect to maximum distribution reduction is obtained and the significance of attributes is defined in decision table, from which a polynomial heuristic algorithm for the optimal maximum distribution reduction is proposed. Finally, the experimental results show that this algorithm is effective and efficient. |
Year | DOI | Venue |
|---|---|---|
2005 | null | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Keywords | Field | DocType |
polynomial heuristic algorithm,maximum distribution reduction,basic content,consistent decision table,decision table,judgment theorem,attribute reduction,optimal attribute reduction,optimal maximum distribution reduction,heuristic algorithm | Discrete mathematics,Mathematical optimization,Decision table,Polynomial,Heuristic (computer science),Computer science,Algorithm,Polynomial method | Conference |
Volume | Issue | ISSN |
3613 LNAI | null | 16113349 |
ISBN | Citations | PageRank |
3-540-28312-9 | 0 | 0.34 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaobing Pei | 1 | 26 | 7.78 |
| Yuanzhen Wang | 2 | 86 | 11.78 |