2009 First Asian Conference on Intelligent Information and Database Systems A Novel Multi-objective Affinity Set Classification System: An Investigation of Delayed Diagnosis Detection Dong hoi, Quang binh, Vietnam April 01-April 03 ISBN: 978-0-7695-3580-7
This paper proposed a novel multi-objective affinity set (MO affinity set) classification system comparing with Ant colony optimization (ACO) and affinity set theory on delayed diagnosis dataset classification. The output of MO affinity set classification rules has the higher accuracy than ACO and traditional affinity set. Furthermore, our MO affinity set classification skips the traditional affinity set k-core method, and has fewer rules. It is better and more easily to apply or to construct a support system if the number of rules is smaller.
Index Terms:
Multi-objective affinity set; Ant colony optimization (ACO); delayed diagnosis detection
Citation:
Chih-Hung Wu, Wei-Ting Li, Chin-Chia Hsu, Chi-Hua Li, I-Ching Fang, Chia-Hsiang Wu, "A Novel Multi-objective Affinity Set Classification System: An Investigation of Delayed Diagnosis Detection," aciids, pp.289-294, 2009 First Asian Conference on Intelligent Information and Database Systems, 2009 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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