Abstract
Influence of projection pursuit on classification errors and estimates of a posteriori probabilities from the sample is considered. Observed random variable is supposed to satisfy a multidimensional Gaussian mixture model. Presented computer simulation results show that for comparatively small sample size classification using projection pursuit algorithm gives better accuracy of estimates of a posteriori probabilities and less classification error.
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