Name
Title | ||
|---|---|---|
An Attribute Reduction Algorithm by Switching Exhaustive and Heuristic Computation of Relative Reducts |
Abstract | ||
|---|---|---|
We propose a heuristic algorithm to compute as many relative reducts as possible from a decision table with numerous condition attributes. The proposed algorithm is based on generating many reduced decision tables that preserve discernibility of objects in the given decision table. Moreover, the proposed algorithm switches exhaustive attribute reduction and heuristic attribute reduction by the number of condition attributes in decision tables. Experimental results indicate that the proposed algorithm can generate many relative reducts from datasets that are difficult to compute all relative reducts. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GrC.2010.147 | Granular Computing |
Keywords | Field | DocType |
decision table,reduced decision table,condition attribute,proposed algorithm,heuristic attribute reduction,switching exhaustive,relative reducts,numerous condition attribute,heuristic computation,exhaustive attribute reduction,attribute reduction algorithm,heuristic algorithm,data analysis,switches,rough set,delta modulation,algorithm design and analysis,decision tables,annealing | Heuristic,Algorithm design,Decision table,Computer science,Heuristic (computer science),Delta modulation,Algorithm,Rough set,Artificial intelligence,Machine learning,Computation | Conference |
ISBN | Citations | PageRank |
978-1-4244-7964-1 | 3 | 0.61 |
References | Authors | |
10 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yasuo Kudo | 1 | 95 | 26.41 |
| Tetsuya Murai | 2 | 186 | 42.10 |