DocumentCode
506869
Title
The Effect of Distance Metrics on Boosting with Dynamic Weighting Schemes
Author
Yang, Xinzhu ; Yuan, Bo ; Liu, Wenhuang
Author_Institution
Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China
Volume
1
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
320
Lastpage
324
Abstract
This paper presents some preliminary experimental results on RegionBoost, which is a typical example of a class of boosting algorithms based on dynamic weighting schemes. It is shown that the performance of RegionBoost with the k-nearest neighbor (kNN) algorithm as the competency predictor of its basic classifiers can be significantly improved on a variety of standard UCI benchmark datasets by using non-Euclidean distance metrics.
Keywords
learning (artificial intelligence); RegionBoost; benchmark datasets; boosting algorithms; distance metrics; dynamic weighting schemes; k-nearest neighbor algorithm; nonEuclidean distance metrics; Boosting; Fuzzy systems; Heuristic algorithms; Supervised learning; Voting; RegionBoost; boosting; dynamic weighting; fractional distance metircs; kNN;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.688
Filename
5358579
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