Name
Abstract | ||
|---|---|---|
Rough set is a new mathematical theory for dealing with uncertain and imprecise information. In view of it widely applied to data analysis, how to measure effectively the uncertainty is a meaningful issue. First, several main methods of uncertainty measure are introduced and their advantages and disadvantages are analyzed and compared; Second, combined with rough entropy, precision, inclusion degree, a new method of uncertainty measure, which is used to measure the uncertainty of rough set, is proposed. Finally, the proposed method is tested and compared with other methods of uncertainty measure. Experimental results show that it is effective and make the uncertainty measure more precise and complete. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/GRC.2008.4664649 | 2008 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, VOLS 1 AND 2 |
Keywords | Field | DocType |
rough set,set theory,entropy,uncertainty,data analysis,rough set theory,information entropy,measurement uncertainty | Set theory,Mathematical optimization,Computer science,Mathematical theory,Measurement uncertainty,Sensitivity analysis,Algorithm,Uncertainty analysis,Rough set,Artificial intelligence,Entropy (information theory),Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taorong Qiu | 1 | 47 | 11.55 |
| Min You | 2 | 0 | 0.34 |
| Hanjuan Ge | 3 | 0 | 0.68 |
| Bin Nie | 4 | 27 | 5.56 |