효율적인 실내 공간 인식을 위한 퍼지 결정 트리의 융합

• Published in: 한국컴퓨터정보학회논문지, 22(4) pp. 33 - 39
• Main Authors: 김기상, 최형일
• Format: Journal Article
• Language: Korean
• Published: 한국컴퓨터정보학회 01.04.2017
• Subjects: 컴퓨터학
• ISSN: 1598-849X; 2383-9945
• DOI: 10.9708/jksci.2017.22.04.033

In this paper, we expand the process of classification to an ensemble of fuzzy decision tree. For indoor space recognition, many research use Boosted Tree, consists of Adaboost and decision tree. The Boosted Tree extracts an optimal decision tree in stages. On each stage, Boosted Tree extracts the good decision tree by minimizing the weighted error of classification. This decision tree performs a hard decision. In most case, hard decision offer some error when they classify nearby a dividing point. Therefore, We suggest an ensemble of fuzzy decision tree, which offer some flexibility to the Boosted Tree algorithm as well as a high performance. In experimental results, we evaluate that the accuracy of suggested methods improved about 13% than the traditional one. KCI Citation Count: 1