Abstract
This paper is concerned with the problem of probability density function estimation using mixture modelling. In [7] and [3], we proposed the Predictive Validation, PV, technique as a reliable tool for the Gaussian mixture model architecture selection. We propose a modified form of the PV method to eliminate underlying problems of the validation test for a large number of test points or very complex models.
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© 2002 Springer-Verlag Berlin Heidelberg
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Sadeghi, M., Kittler, J. (2002). Modified Predictive Validation Test for Gaussian Mixture Modelling. In: Caelli, T., Amin, A., Duin, R.P.W., de Ridder, D., Kamel, M. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2002. Lecture Notes in Computer Science, vol 2396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70659-3_43
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DOI: https://doi.org/10.1007/3-540-70659-3_43
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