Combining diverse classifiers using precision index functions Online publication date: Thu, 31-Jul-2014
by Jose Bird; Daijin Ko
International Journal of Applied Pattern Recognition (IJAPR), Vol. 1, No. 1, 2013
Abstract: This paper introduces a combining classifier using two proposed precision indexes: precision index (PIN) and class specific precision index (PIC). Comparison of combining methods typically fails to consider high precision performance. This new combining method generates predictions with higher precision and recall than other methods. The proposed method is especially useful for efficient screening of predictions where actual verification is time consuming and costly. The performance of the proposed method is compared to majority voting, stacking, and cluster-selection for two well-known datasets: 1) vowel recognition (Hastie et al., 2009); 2) yeast protein localisation (Frank and Asuncion, 2010). The precisions obtained exceeded results previously reported for protein localisation data (Horton and Nakai, 1997; Chen, 2010) and for vowel recognition data (Hastie et al., 2009). A weighted precision index using PIC and PIN indexes outperformed all combining methods at higher precisions.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Applied Pattern Recognition (IJAPR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook