文献の詳細

論文の言語	英語
著者	Masakazu Iwamura, Shinichiro Omachi, and Hirotomo Aso
論文名	On the Bias of Predictive Distribution in Pattern Recognition
論文誌名	Systems and Computers in Japan
Vol.	36
No.	5
ページ	pp.45-54
出版社	John Wiley & Sons, Inc.
査読の有無	無
年月	2005年5月
要約	To estimate distribution from training samples, the maximum likelihood estimation treats the unknown parameter of the distribution as a constant. On the other hand, Bayesian estimation treats the parameter as a random variable. In pattern recognition, Bayesian estimation has been known to improve recognition accuracy. However, it was pointed out that the Bayesian estimation is not effective due to the bias of the likelihood when sample sizes of classes are not the same. In this paper, we show recognition accuracy is improved by modifying the bias of the likelihood when sample sizes are not the same. This indicates that the cause of the ineffectiveness is the bias. We derive the formula of the bias of Geisser's predictive distribution without any approximation, and show a way of modification of the bias of the likelihood. We confirm effectiveness of the proposed method in experiments. In addition, the derived formula gives the theoretical background of a known empirical knowledge.

• 注記
  PDF file is available at http://www3.interscience.wiley.com/cgi-bin/jissue/110429145.
• BibTeX用エントリー

  @Article{Iwamura2005,
    author =	{Masakazu Iwamura and Shinichiro Omachi and Hirotomo Aso},
    title =	{On the Bias of Predictive Distribution in Pattern Recognition},
    journal =	{Systems and Computers in Japan},
    year =	2005,
    month =	may,
    volume =	{36},
    number =	{5},
    pages =	{45--54},
    publisher =	{John Wiley \& Sons, Inc.}
  }
  
  
  

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