Texto completo
![[thumbnail of 9939358.pdf]](https://oa.upm.es/style/images/fileicons/application_pdf.png) |
PDF (Portable Document Format)
- Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (48kB) |
Feature space parameterization by means self-organization maps and Box–Cox transformations
Cita
Platero Dueñas, Carlos 
ORCID: https://orcid.org/0000-0003-3712-8297
(1997).
Feature space parameterization by means self-organization maps and Box–Cox transformations.
En: "VII National Symposium on Pattern Recognition and Image Analysis", 23-25 april 1997, Universitat Autònoma de Barcelona, Spain. ISBN 84-922529-0-1.
ORCID: https://orcid.org/0000-0003-3712-8297
(1997).
Feature space parameterization by means self-organization maps and Box–Cox transformations.
En: "VII National Symposium on Pattern Recognition and Image Analysis", 23-25 april 1997, Universitat Autònoma de Barcelona, Spain. ISBN 84-922529-0-1.
Descripción
| Título: | Feature space parameterization by means self-organization maps and Box–Cox transformations |
|---|---|
| Autor/es: |
|
| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | VII National Symposium on Pattern Recognition and Image Analysis |
| Fechas del Evento: | 23-25 april 1997 |
| Lugar del Evento: | Universitat Autònoma de Barcelona, Spain |
| Título del Libro: | Pattern recognition and image analysis : $bpreprints of the VII National Symposium on Pattern Recognition and Image Analysis |
| Fecha: | 1 Enero 1997 |
| ISBN: | 84-922529-0-1 |
| Materias: | |
| Escuela: | E.T.S.I. Diseño Industrial (UPM) |
| Departamento: | Ingeniería Eléctrica, Electrónica Automática y Física Aplicada |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
This paper shows a new method for implement hybrid classifiers, they are supported by self-organizing maps and parametric approach. The first are used to data analysis by means SOM, U-Matrix and approximation to typical density functions. The space parametrization is based on marginal Box-Cox transformations. The optimal feature space is determined by maximizing the Bhattacharyya∋s distance. The effect of size samples is considered. This method has been employed in the classification of visual defects in cast aluminium. Traditional classifiers as LVQ, MLP, and systems based on rules had been implemented.
Más información
| ID de Registro: | 93630 |
|---|---|
| Identificador DC: | https://oa.upm.es/93630/ |
| Identificador OAI: | oai:oa.upm.es:93630 |
| URL Portal Científico: | https://portalcientifico.upm.es/es/ipublic/item/9939358 |
| Depositado por: | iMarina Portal Científico |
| Depositado el: | 03 Feb 2026 13:53 |
| Ultima Modificación: | 03 Feb 2026 13:53 |
Acciones
- Estadísticas
- Exportar cita
- Editar (sólo personal del Archivo)
