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https://ah.lib.nccu.edu.tw/handle/140.119/74371
題名: | Generalized Bradley-Terry Models and Multi-Class Probability Estimates | 作者: | Weng, Ruby C.;Huang, Tzu-kuo;Lin, Chih-jen 翁久幸 |
貢獻者: | 統計系 | 關鍵詞: | Bradley-Terry model; probability estimates; error correcting output codes; support vector machines | 日期: | 2006 | 上傳時間: | 7-Apr-2015 | 摘要: | 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. | 關聯: | Journal of Machine Learning Research - JMLR , vol. 7, pp. 85-115 | 資料類型: | article |
Appears in Collections: | 期刊論文 |
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