Utilizing an enhanced cellular automata model for data mining
Data mining deals with clustering and classifying large amounts of data, in order to discover new knowledge from the existent data by identifying correlations and relationships between various data-sets. Cellular automata have been used before for classification purposes. This paper presents a cellu...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/666491 |
| Acceso en línea: | http://hdl.handle.net/10486/666491 |
| Access Level: | acceso abierto |
| Palabra clave: | Cellular Automata Clustering Classification Data Mining Moore Neighborhood Informática |
| Sumario: | Data mining deals with clustering and classifying large amounts of data, in order to discover new knowledge from the existent data by identifying correlations and relationships between various data-sets. Cellular automata have been used before for classification purposes. This paper presents a cellular automata enhanced classification algorithm for data mining. Experimental results show that the proposed enhancement gives better performance in terms of accuracy and execution time than previous work using cellular automata. |
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