Title :
Combining one class classification models for avian influenza outbreaks
Author :
Zhang, Jie ; Lu, Jie ; Zhang, Guangquan
Author_Institution :
Centre for Quantum Comput. & Intell. Syst., Univ. of Technol., Sydney, NSW, Australia
Abstract :
The prediction of avian influenza outbreak animal cases is a genuine one class classification issue because the real world outliers are impractical to obtain. In this paper, a new combining one class classification method has been presented and illustrated on the avian influenza outbreak dataset. The presented combining methods outperform the previous combining methods both on the original avian influenza outbreak dataset and dimension reduction one. The new one classification combining model can be adapted to the warning surveillance purpose and proved to be practical on the avian influenza outbreak prediction tasks.
Keywords :
alarm systems; diseases; pattern classification; avian influenza outbreak animal cases; one class classification models; warning surveillance; Analytical models; Birds; Data models; Diseases; Influenza; Training; One class classification model; avian influenza; combining model; prediction; warning;
Conference_Titel :
Computational Intelligence in Multicriteria Decision-Making (MDCM), 2011 IEEE Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-61284-068-0
DOI :
10.1109/SMDCM.2011.5949278