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The Optimum Classifier and the Performance Evaluation by Bayesian Approach
http://hdl.handle.net/10076/11095
http://hdl.handle.net/10076/11095d335fb97-1ad0-489b-a128-068eb565b58f
名前 / ファイル | ライセンス | アクション |
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40A12189.pdf (264.6 kB)
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2010-05-24 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | The Optimum Classifier and the Performance Evaluation by Bayesian Approach | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Statistical pattern recognition | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Optimum classifier | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Monte Carlo simulation | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Bayesian approach | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
資源タイプ | conference paper | |||||
著者 |
Han, Xuexian
× Han, Xuexian× Wakabayashi, Tetsushi× Kimura, Fumitaka |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | This paper deals with the optimum classifier and the performance evaluation by the Bayesian approach. Gaussian population with unknown parameters is assumed. The conditional density given a limited sample of the population has a relationship to the multivariate t-distribution. The mean error rate of the optimum classifier is theoretically evaluated by the quadrature of the conditional density. To verify the optimality of the classifier and the correctness of the mean error calculation, the results of Monte Carlo simulation employing a new sampling procedure are shown. It is also shown by the comparative study that the Bayesian formulas of the mean error rate have the following characteristics. 1) The unknown population parameters are not required in its calculation. 2) The expression is simple and clearly shows the limited sample effect on the mean error rate. 3) The relationship between the prior parameters and the mean error rate is explicitly expressed. |
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内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Berlin | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 901 | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Advances in pattern recognition : joint IAPR International Workshops SSPR 2000 and SPR 2000, Alicante, Spain, August 30-September 1, 2000 : proceedings | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Lecture notes in computer science | |||||
書誌情報 |
巻 1876, p. 591-600, 発行日 2000-01-01 |
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ISBN | ||||||
識別子タイプ | ISBN | |||||
関連識別子 | 9783540679462 | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1007/3-540-44522-6_61 | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||
日本十進分類法 | ||||||
主題Scheme | NDC | |||||
主題 | 007 | |||||
出版者 | ||||||
出版者 | Springer | |||||
関係URI | ||||||
関連名称 | http://www.springerlink.com/content/e01h3er836575j22/?p=19a80a405b4e41c0ac38969c79bf900eπ=88 | |||||
ノート | ||||||
出版者版電子ジャーナルあり | ||||||
資源タイプ(三重大) | ||||||
Conference Paper / 会議発表論文 |