Classification with multiple independent measurements under a separate sampling scheme

In this article, we consider the problem of classifying mm independent repeated (multiple) observations coming from the same population under a separate sampling scheme. We derive the asymptotic risk of the proposed NN type classification rule and obtain the upper and lower bounds for it in specific cases in terms of Bayes risk. Using a Monte Carlo simulation study we show that, as mm increases, the classification risk decreases.