Title :
Software Reliability Prediction Model Based on Relevance Vector Machine
Author_Institution :
Dept. of Comput. Sci. & Inf. Technol., ZheJiang Wanli Univ., Ningbo, China
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;
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
DOI :
10.1109/SKG.2010.49