Multivariate data analysis based on the ωkn-criteria and multilayer perceptron

A comparative study of multidimensional classifiers based on the goodness-of-fit criteria ωkn and multilayer perceptrons (MLP) has been carried out. It is shown that MLP exhibits the “instantaneous” learning effect and improves the quality of recognition in the case of input data represented in the form of variational series. The reasons are analyzed that underlie these effects. Recommendations for joint usage of the ωkn criteria and of MLPs are given.