DocumentCode
3521166
Title
Software Reliability Prediction Model Based on Relevance Vector Machine
Author
Zheng, Qiuhong
Author_Institution
Dept. of Comput. Sci. & Inf. Technol., ZheJiang Wanli Univ., Ningbo, China
fYear
2010
fDate
1-3 Nov. 2010
Firstpage
317
Lastpage
320
Abstract
Relevance vector machines have been successfully used in many domains, while their application in software reliability prediction is still quite rare. In this work, we propose to apply support vector regression (SVR) to build software reliability prediction model (RVMSRPM). We also compare the prediction accuracy of software reliability prediction models based on RVM, SVM, ANN and three traditional NHPP models. Experimental results show that our proposed RVM-based software reliability prediction model could achieve a higher prediction accuracy compared with these models.
Keywords
neural nets; prediction theory; regression analysis; software reliability; support vector machines; relevance vector machine; software reliability prediction model; support vector regression;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantics Knowledge and Grid (SKG), 2010 Sixth International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-8125-5
Electronic_ISBN
978-0-7695-4189-1
Type
conf
DOI
10.1109/SKG.2010.49
Filename
5663537
Link To Document