DYNAMIC STATISTICAL CLASSIFICATION

• Main Authors: JAVIER PULIDO CEJUDO, CARLOS CUEVAS COVARRUBIAS
• Format: Article
• Language: Spanish
• Published: Universidad de Costa Rica 2017-01-01
• Series: Revista de Matemática: Teoría y Aplicaciones
• Subjects: supervised statistical classification; multivariate normal distribution; vector fields; attractors; bifurcation; dynamical systems
• Online Access: https://revistas.ucr.ac.cr/index.php/matematica/article/view/27774

We consider the statistical supervised classification problem from adynamical 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 then 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 ofthem. 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.