Repeated Observations for Classification

07/19/2023

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by   Hüseyin Afşer, et al.

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We study the problem nonparametric classification with repeated observations. Let be the d dimensional feature vector and let Y denote the label taking values in {1,… ,M}. In contrast to usual setup with large sample size n and relatively low dimension d, this paper deals with the situation, when instead of observing a single feature vector we are given t repeated feature vectors _1,… ,_t. Some simple classification rules are presented such that the conditional error probabilities have exponential convergence rate of convergence as t→∞. In the analysis, we investigate particular models like robust detection by nominal densities, prototype classification, linear transformation, linear classification, scaling.