Ponencia
Supervised Learning Using Instance-based Patterns
Autor/es | Serendero Sáez, Santiago Patricio
Toro Bonilla, Miguel |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2001-11 |
Fecha de depósito | 2023-01-26 |
Publicado en |
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Resumen | This paper introduces a new classification algorithm of the instance-based learning type. Training records are converted into patterns associated with a known class label, and stored permanently into a trie1-like tree ... This paper introduces a new classification algorithm of the instance-based learning type. Training records are converted into patterns associated with a known class label, and stored permanently into a trie1-like tree structure along with other helpful information. Classifying new records is done selecting from the trie two best patterns as solutions hypotheses. Best pattern selection is done using standard distance metrics, a strength function and an exclusive values concept. Classification tests done on several data files have shown very accurate results. |
Cita | Serendero Sáez, S.P. y Toro Bonilla, M. (2001). Supervised Learning Using Instance-based Patterns. En CAEPIA 2001: IX Conferencia de la Asociación Española para la Inteligencia Artificial Gijón, España: Asociación Española para la Inteligencia Artificial. |
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