Abstract
In this paper, we discuss sensitivity analysis in linear subspace method, especially on multiple-case diagnostics.
Linear subspace method by Watanabe (1973) is a useful discriminant method in the field of pattern recognition. We have proposed its sensitivity analyses, with single-case diagnostics and multiple-case diagnostics with PCA.
We propose a modified multiple-case diagnostics using clustering and discuss its effectiveness with numerical simulations.
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References
CRITCHLEY, F. (1985): Influence in principal component analysis.Biometrika, 72, 627-636.
HAMPEL, F. R. (1974): The influence curve and its role in robust estimation. Journal of the American Statistical Association, 69, 383-393.
HAMPEL, F. R., RONCHETTI, E. M., ROUSSEEOUW, P. J. and STAHEL, W. A. (1986): Robust statistics the approach based on influence functions. Jhon Wiley & Sons New York.
HAYASHI, K., TANAKA, Y. and MIZUTA, M. (2008): Sensitivity analysis in subspace method of the identification problem in multiclass classification. Proceedings of 2008 Korea-Japan Statistics Conference of Young Researchers Wakimoto Memorial Fund, 63-75, Korea University, Seoul, Korea.
RADHAKRISHAN, R. and KSHIRSAGAR, A. M. (1981): Influence functions for certain parameters in multivariate analysis. Communications in Statistics, A 10, 515-529.
TANAKA, Y. (1988): Sensitivity analysis in principal component analysis: Influence on the subspace spanned by principal components. Communications in Statistics, A 17, 3157-3175.
TANAKA, Y. (1994): Recent advance in sensitivity analysis in multivariate statistical methods. Journal of the Japanese Society of Computational Statistics, 7, 1-25.
WATANABE, S. (1970): Featuring compression. Advances in Information Systems Science Volume 3 (Edited by Tou, J. T.), Plenum Press, New York.
WATANABE, S., LAMPERT, P. F., KULIKOWSKI, C. A., BUXTON, J. L. and Walker, R. (1967): Evaluation and selection of variables in pattern recognition. Computer and Information Sciences II, Academic Press, New York.
WATANABE, S. and PAKVASA, N. (1973): Subspace method of pattern recognition, Proceedings of 1st International Joint Conference of Pattern Recognition, 25-32.
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Hayashi, K., Minami, H., Mizuta, M. (2010). On Multiple-Case Diagnostics in Linear Subspace Method. In: Lechevallier, Y., Saporta, G. (eds) Proceedings of COMPSTAT'2010. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2604-3_49
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DOI: https://doi.org/10.1007/978-3-7908-2604-3_49
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