Dynamic statistical classification
Guardado en:
| Autores: | , |
|---|---|
| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2017 |
| Descripción: | 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 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 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. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Inglés |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/27774 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/27774 |
| Access Level: | acceso abierto |
| Palabra clave: | supervised statistical classification multivariate normal distribution vector fields attractors bifurcation dynamical systems Clasificación estadística supervisada distribución normal multivariada campos vectoriales atractores bifurcación sistemas dinámicos |