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政大機構典藏 > 商學院 > 統計學系 > 期刊論文 > Item 140.119/74371

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/74371

Title:	Generalized Bradley-Terry Models and Multi-Class Probability Estimates
Authors:	Weng, Ruby C.;Huang, Tzu-kuo;Lin, Chih-jen 翁久幸
Contributors:	統計系
Keywords:	Bradley-Terry model;probability estimates;error correcting output codes;support vector machines
Date:	2006
Issue Date:	2015-04-07 17:02:11 (UTC+8)
Abstract:	The Bradley-Terry model for obtaining individual skill from paired comparisons has been popular in many areas. In machine learning, this model is related to multi-class probability estimates by coupling all pairwise classification results. Error correcting output codes (ECOC) are a general framework to decompose a multi-class problem to several binary problems. To obtain probability estimates under this framework, this paper introduces a generalized Bradley-Terry model in which paired individual comparisons are extended to paired team comparisons. We propose a simple algorithm with convergence proofs to solve the model and obtain individual skill. Experiments on synthetic and real data demonstrate that the algorithm is useful for obtaining multi-class probability estimates. Moreover, we discuss four extensions of the proposed model: 1) weighted individual skill, 2) home-field advantage, 3) ties, and 4) comparisons with more than two teams.
Relation:	Journal of Machine Learning Research - JMLR , vol. 7, pp. 85-115
Data Type:	article
Appears in Collections:	[統計學系] 期刊論文

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