| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Outline of Final Research Achievements |
It is known that the optimum nonlinear discriminant mapping can be defined as a linear combination of the Bayesian a posterior probabilities and the coefficients of the linear combination are obtained by solving the eigenvalue problem of the matrices defined by using the Bayesian a posterior probabilities. We derived the optimum kernel function (discriminant kernel) which were used in the optimum nonlinear discriminate mapping. It is also defined by using the posterior probabilities. For real applications, we have to estimate the posterior probabilities. In this study, we proposed several nonlinear discriminant analysis methods in which the probabilities were estimated by multinomial logistic regression or K nearest neighbors methods etc. To improve the generalization ability, the probabilities were estimated with regularization. Several applications of the image recognition or image retrieval were also tried.
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