Joint Sub-classifiers One Class Classification Model For Avian Influenza Outbreak Detection

Imperial College Press
Publication Type:
Journal Article
International Journal of Computational Intelligence and Applications, 2011, 10 (4), pp. 425 - 443
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H5N1 avian influenza outbreak detection is a significant issue for early warning of epidemics. This paper proposes domain knowledge-based joint one class classification model for avian influenza outbreak. Instead of focusing on manipulations of the one class classification model, we delve into the one class avian influenza dataset, divide it into subclasses by domain knowledge, train the sub-class classifiers and unify the result of each classifier. The proposed joint method solves the one class classification and features selection problems together. The experiment results demonstrate that the proposed joint model definitely outperforms the normal one class classification model on the animal avian influenza dataset.
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