Title
Joint Sub-Classifiers One Class Classification Model For Avian Influenza Outbreak Detection
Abstract
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.
Year
DOI
Venue
2011
10.1142/S1469026811003173
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS
Keywords
Field
DocType
One class classification, avian influenza, outbreak detection, joint model
Warning system,One-class classification,Domain knowledge,Pattern recognition,Computer science,Outbreak,Artificial intelligence,Influenza A virus subtype H5N1,Classifier (linguistics),Machine learning
Journal
Volume
Issue
ISSN
10
4
1469-0268
Citations 
PageRank 
References 
0
0.34
25
Authors
3
Name
Order
Citations
PageRank
Jie Zhang14715.01
Jie Lu2112592.04
Guangquan Zhang31973145.64