Dynamic statistical classification
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| Autorzy: | , |
|---|---|
| Format: | artículo original |
| Status: | Versión publicada |
| Data wydania: | 2017 |
| Opis: | 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. |
| Kraj: | Portal de Revistas UCR |
| Instytucja: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Język: | Inglés |
| OAI Identifier: | oai:archivo.portal.ucr.ac.cr:article/27774 |
| Dostęp online: | https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/27774 |
| Słowo kluczowe: | supervised statistical classification multivariate normal distribution vector fields attractors bifurcation dynamical systems Clasificación estadística supervisada distribución normal multivariada campos vectoriales atractores bifurcación sistemas dinámicos |