Name
Title | ||
|---|---|---|
Variable precision bayesian rough set model and its application to human evaluation data |
Abstract | ||
|---|---|---|
This paper focuses on a rough set method to analyze human evaluation data with much ambiguity such as sensory and feeling data. In order to handle totally ambiguous and probabilistic human evaluation data, we propose a probabilistic approximation based on information gains of equivalent classes. Furthermore, we propose a two-stage method to simply extract uncertain if–then rules using decision functions of approximate regions. Finally, we applied the proposed method to practical human sensory evaluation data and examined the effectiveness of the proposed method. The result shown that our proposed rough set method is more applicable to human evaluation data. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11548669_31 | RSFDGrC (1) |
Keywords | Field | DocType |
rough set method,practical human sensory evaluation,probabilistic human evaluation data,decision function,two-stage method,proposed rough set method,rough set model,human evaluation data,variable precision bayesian,probabilistic approximation,approximate region,rough set,sensory evaluation,information gain | Data mining,Decision table,Computer science,Artificial intelligence,Probabilistic logic,Ambiguity,Decision rule,Decision matrix,Pattern recognition,Variable precision,Rough set,Machine learning,Bayesian probability | Conference |
Volume | ISSN | ISBN |
3641 | 0302-9743 | 3-540-28653-5 |
Citations | PageRank | References |
12 | 1.11 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tatsuo Nishino | 1 | 16 | 2.01 |
| Mitsuo Nagamachi | 2 | 66 | 19.26 |
| Hideo Tanaka | 3 | 84 | 8.70 |