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http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1389| A review of instance selection methods | |
| JOSE ARTURO OLVERA LOPEZ JESUS ARIEL CARRASCO OCHOA JOSE FRANCISCO MARTINEZ TRINIDAD Josef Kittler | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| In supervised learning, a training set providing previously known information is used to classify new instances. Commonly, several instances are stored in the training set but some of them are not useful for classifying therefore it is possible to get acceptable classification rates ignoring non useful cases; this process is known as instance selection. Through instance selection the training set is reduced which allows reducing runtimes in the classification and/or training stages of classifiers. This work is focused on presenting a survey of the main instance selection methods reported in the literature. | |
| Springer Science+Business Media B.V. | |
| 2010 | |
| Artículo | |
| Inglés | |
| Estudiantes Investigadores Público en general | |
| Olvera-López, J.A., et al., (2010). A review of instance selection methods, Artificial Intelligence Review. (34):133–143 | |
| CIENCIA DE LOS ORDENADORES | |
| Versión aceptada | |
| acceptedVersion - Versión aceptada | |
| Aparece en las colecciones: | Artículos de Ciencias Computacionales |
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