Selective sequencial integration on classification
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Ferreira, Carlos [1] ; Gama, João [1]
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[1] Universidade Do Porto
Universidade Do Porto
Santo Ildefonso, Portugal
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- Localización: XII Conferencia de la Asociación Española para la Inteligencia Artificial: (CAEPIA 2007). Actas / coord. por Daniel Borrajo Millán, Luis Castillo Vidal, Juan Manuel Corchado Rodríguez, Vol. 1, 2007, ISBN 978-84-611-8847-5, págs. 337-346
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
To solve a classification problem we propose an algorithm that integrates sequencially Apriori association rule miner with C4.5 decision tree induction algorithm. This methodology uses constructive induction to extend primitive description language with interesting attributes. New attributes are selected frequent itemsets found using Apriori. Also we study the effect of different selection filters in algorithm accuracy and complexity. The experimental evaluation demonstrated that the proposed methodology generates high accurate and compact models. The best results were obtained using Pearson-correlation and heuristics from information theory as selection measures.
