A Cost-sensitive Intelligent Prediction Model for Outsourced Software Project Risk

摘要：

　　Outsourced software project is one of the main ways of software development,which is of high failure rate.Intelligent risk prediction model can help identify high risk project in time.However,the existing models are mostly based on such a hypothesis that all the cost of misclassification is equal,which is not consistont with the reality that in the domain of software project risk prediction,the cost of predicting a fail-prone project as a success-prone project is different from predicting a success-prone project as a fail-prone project.To the best of our knowledge,the cost-sensitive learning method has not yet been applied in the domain of outsonrced software project risk management though it has been widely used in a variety of fields.Based on this situation,we selected five classifiers,and introduced cost-sensitive learning method to build intelligent prediction models respectively.This paper totally collected 292 real data of outsourced software project for modeling.Experiment results showed that,under cost-sensitive scenario,the polynomial kernel support vector machine is the best classifier for ontsonrced software project risk prediction among the five classifiers due to its high prediction accuracy,stability and low cost.

关键词： Outsonrced software project Risk management Cost-sensitive Risk prediction

作者: Hongming Zhang Xizhu Mo Lijun Su Bin Feng Xiangzhou Zhang Yong Hu

作者单位: Business Intelligence and Knowledge Discovery, School of Business Guangdong University of Foreign Studies, Guangzhou, 510006, China

会议类型: 国际会议

会议名称: The Twelfth Wuhan International Conference on E-Business(第十二届武汉电子商务国际会议)

会议地点: 武汉

会议语种:英文

页码: 379-385

在线出版日期: 2013-05-25（万方平台首次上网日期，不代表论文的发表时间）