Sedàs: a semantic based general classifier system
In this work we present the general classifier system Sedàs. We show how this system implements the description of the domain and how it builds similarity matrices and classification trees. The system uses a new semantics, introduced in [Torra96], to define a distance between qualitative values.
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 1997 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/3493 |
| Acceso en línea: | https://hdl.handle.net/2099/3493 |
| Access Level: | acceso abierto |
| Palabra clave: | Clustering Knowledge representation Knowledge-based systems Sedàs Intel·ligència artificial Sistemes experts (Informàtica) Cluster, Anàlisi de Classificació AMS::68 Computer science::68T Artificial intelligence |
| Sumario: | In this work we present the general classifier system Sedàs. We show how this system implements the description of the domain and how it builds similarity matrices and classification trees. The system uses a new semantics, introduced in [Torra96], to define a distance between qualitative values. |
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