Name
Title | ||
|---|---|---|
Heuristic Algorithm For Attribute Reduction Based On Classification Ability By Condition Attributes |
Abstract | ||
|---|---|---|
The heuristic algorithm we propose to compute a relative reduct candidate is based on evaluating classification ability of condition attributes. Considering the discernibility and equivalence of objects for condition attributes in relative reducts, we introduce evaluation criteria for condition attributes and relative reducts. The computational complexity of the proposed algorithm is O(vertical bar U vertical bar(2)vertical bar C vertical bar(2)). Experimental results indicate that our algorithm often generates a relative reduct producing a good evaluation result. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.20965/jaciii.2011.p0102 | JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS |
Keywords | Field | DocType |
rough set, attribute reduction, heuristic algorithm, classification ability | Data mining,Reduct,Pattern recognition,Computer science,Heuristic (computer science),Rough set,Equivalence (measure theory),Artificial intelligence,Null-move heuristic,Machine learning,Computational complexity theory | Journal |
Volume | Issue | ISSN |
15 | 1 | 1343-0130 |
Citations | PageRank | References |
2 | 0.42 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yasuo Kudo | 1 | 95 | 26.41 |
| Tetsuya Murai | 2 | 186 | 42.10 |