NLC: A Measure Based on Projections
In this paper, we propose a new feature selection criterion. It is based on the projections of data set elements onto each attribute. The main advantages are its speed and simplicity in the evaluation of the attributes. The measure allows features to be sorted in ascending order of importance in the...
| Autores: | , , |
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| Tipo de documento: | capítulo de livro |
| Estado: | Versão publicada |
| Data de publicação: | 2003 |
| País: | España |
| Recursos: | Universidad de Sevilla (US) |
| Repositório: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/39327 |
| Acesso em linha: | http://hdl.handle.net/11441/39327 https://doi.org/10.1007/978-3-540-45227-0_88 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Data Structures Cryptology and Information Theory Artificial Intelligence (incl. Robotics) Database Management Information Storage and Retrieval Information Systems Applications (incl. Internet) Multimedia Information Systems |
| Resumo: | In this paper, we propose a new feature selection criterion. It is based on the projections of data set elements onto each attribute. The main advantages are its speed and simplicity in the evaluation of the attributes. The measure allows features to be sorted in ascending order of importance in the definition of the class. In order to test the relevance of the new feature selection measure, we compare the results induced by several classifiers before and after applying the feature selection algorithms. |
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