러프 집합을 이용한 의사결정나무의 노드 선택 방법

• 영문명: Approach to selection of nodes of decision tree using Rough Set
• 발행기관: 한국산업경영시스템학회
• 저자명: 유재진 김재련
• 간행물 정보: 『한국산업경영시스템학회 학술대회』2003년 추계학술대회 논문집, 41~46쪽, 전체 6쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2003.10.01

영문 초록

  Classification is an important area in a data mining. There are various ways in classification methodologies : the decision tree and the neural network, etc. Recently, Rough set theory has been presented as a method for classification. Rough set theory is a new approach in decision making in the presence of uncertainty and vagueness. In the process of constructing the tree, appropriate attributes have to be selected as nodes of the tree. In this paper, we present a new approach to selection of attributes for the construction of decision tree using the Rough set theory. The suggested method makes more simple classification rules in the decision tree and reduces the volume of the data to be treated.

목차

Abstract
1. 서론
2. 기존 연구 고찰
3. 본 연구에서 제안하는 RSC알고리즘
4. 결론
참고 문헌

키워드

러프 집합 의사결정나무 데이터 마이닝