대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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- Pages.672-674
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- 2000
러프집합과 Granular Computing을 이용한 분류지식 발견
Discovering classification knowledge using Rough Set and Granular Computing
- Choi, Sang-Chul (Department of Electrical Engineering, Kangwon National University) ;
- Lee, Chul-Heui (Department of Electrical Engineering, Kangwon National University)
- 발행 : 2000.11.25
초록
There are various ways in classification methodologies of data mining such as neural networks but the result should be explicit and understandable and the classification rules be short and clear. Rough set theory is a effective technique in extracting knowledge from incomplete and inconsistent information and makes an offer classification and approximation by various attributes with effect. This paper discusses granularity of knowledge for reasoning of uncertain concepts by using generalized rough set approximations based on hierarchical granulation structure and uses hierarchical classification methodology that is more effective technique for classification by applying core to upper level. The consistency rules with minimal attributes is discovered and applied to classifying real data.
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