Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Model Validation for Model Selection
ICAPR '01 Proceedings of the Second International Conference on Advances in Pattern Recognition
Model Complexity Validation for PDF Estimation Using Gaussian Mixtures
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
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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.