Dynamic statistical classification
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 functi...
| Authors: | , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2017 |
| Country: | Costa Rica |
| Institution: | Universidad de Costa Rica |
| Repository: | Portal de Revistas UCR |
| Language: | English |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/27774 |
| Online Access: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/27774 |
| Access Level: | Open access |
| Keyword: | supervised statistical classification multivariate normal distribution vector fields attractors bifurcation dynamical systems Clasificación estadística supervisada distribución normal multivariada campos vectoriales atractores bifurcación sistemas dinámicos |
| Summary: | 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. |
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