A Study of Parametric and Nonparametric Kernel Density Discrimination (poster presentation)
| Title in English | A Study of Parametric and Nonparametric Kernel Density Discrimination |
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| Authors | |
| Year of publication | 2004 |
| Type | Article in Proceedings |
| Conference | COMPSTAT 2004 - Proceedings in Computational Statistics |
| MU Faculty or unit | |
| Citation | |
| Web | PHOTO GALLERY OF POSTERS |
| Field | Applied statistics, operation research |
| Keywords | linear and quadratic discriminant analysis; nonparametric discriminant analysis; kernel density estimation; product kernels; bandwidth choice |
| Description | This paper compares the performance of parametric and nonparametric discrimination. The multivariate product Gaussian and polynomial kernels with various data-driven choices of the bandwidth are used for density estimators and this nonparametric approaches are compared with classical one by some real and simulated data. The Matlab software environment is used for preprocessing the data and to implement proposed classification methodology. A great attention is focused to the visualization of results. |
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