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http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/2274| Decision tree based classifiers for large datasets | |
| Anilú Franco Arcega Jesús Ariel Carrasco Ochoa GUILLERMO SANCHEZ DIAZ José Francisco Martínez Trinidad | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| In this paper, several algorithms have been developed for building decision trees from large datasets. These algorithms overcome some restrictions of the most recent algorithms in the state of the art. Three of these algorithms have been designed to process datasets described exclusively by numeric attributes, and the fourth one, for processing mixed datasets. The proposed algorithms process all the training instances without storing the whole dataset in the main memory. Besides, the developed algorithms are faster than the most recent algorithms for building decision trees from large datasets, and reach competitive accuracy rates. | |
| Computación y Sistemas | |
| 2013 | |
| Artículo | |
| Inglés | |
| Estudiantes Investigadores Público en general | |
| Franco-Arcega, A., et al., (2013). Decision tree based classifiers for large datasets, Computación y Sistemas, Vol. 15 (2): 95-102 | |
| CIENCIA DE LOS ORDENADORES | |
| Versión aceptada | |
| acceptedVersion - Versión aceptada | |
| Aparece en las colecciones: | Artículos de Ciencias Computacionales |
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| 191. Decision Tree based Classifiers for Large Datasets.pdf | 371.38 kB | Adobe PDF | Visualizar/Abrir |