Abstract

PULIDO-CEJUDO, Javier  and  CUEVAS-COVARRUBIAS, Carlos. Dynamic statistical classification. Rev. Mat [online]. 2017, vol.24, n.1, pp.115-127. ISSN 1409-2433.  http://dx.doi.org/10.15517/rmta.v24i1.27774.

We consider the statistical supervised classification problem from a dynamical systems approach. We assume that two classes exist and that, for each one, a multivariate normal distribution determines the probability to be in a certain region in the n dimensional real vector space. These density functions are the potentials of corresponding gradient vector fields for each class; we construct a “classifying vector field” as a suitable weighted mean of them. From data known in the literature, we estimate the population parameters, and the classes are successfully distinguished; we compute and present confusion matrices. A one and two-dimensional analysis is given.

Keywords : supervised statistical classification; multivariate normal distribution; vector fields; attractors; bifurcation; dynamical systems.

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