Capítulo de Libro
Heuristic Search over a Ranking for Feature Selection
Autor/es | Ruiz Sánchez, Roberto
Riquelme Santos, José Cristóbal Aguilar Ruiz, Jesús Salvador |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2005 |
Fecha de depósito | 2016-04-07 |
Publicado en |
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Resumen | In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in high dimensional data sets. Our method is based ... In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in high dimensional data sets. Our method is based on the relevance and redundancy idea, in the sense that a ranked-feature is chosen if additional information is gained by adding it. This heuristic leads to considerably better accuracy results, in comparison to the full set, and other representative feature selection algorithms in twelve well–known data sets, coupled with notable dimensionality reduction. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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Heuristic search.pdf | 137.5Kb | [PDF] | Ver/ | |