东南大学学报（英文版）2018，Vol.34Issue(3)：295-302,8.DOI:10.3969/j.issn.1003-7985.2018.03.003
面向基于类比的软件工作量估算的多目标特征选择方法
Analogy-based software effort estimation using multi-objective feature selection
摘要
Abstract
The feature selection in analogy-based software effort estimation (ASEE) is formulized as a multi-objective optimization problem.One objective is designed to maximize the effort estimation accuracy and the other objective is designed to minimize the number of selected features.Based on these two potential conflict objectives,a novel wrapperbased feature selection method,multi-objective feature selection for analogy-based software effort estimation (MASE),is proposed.In the empirical studies,77 projects in Desharnais and 62 projects in Maxwell from the real world are selected as the evaluation objects and the proposed method MASE is compared with some baseline methods.Final results show that the proposed method can achieve better performance by selecting fewer features when considering MMRE (mean magnitude of relative error),MdMRE (median magnitude of relative error),PRED (0.25),and SA (standardized accuracy) performance metrics.关键词
软件工作量估算/多目标优化/基于案例的推理/特征选择/实证研究Key words
software effort estimation/multi-objective optimization/case-based reasoning/feature selection/empirical study分类
信息技术与安全科学引用本文复制引用
陈翔,陆凤燕,沈宇翔,谢隽丰,文万志..面向基于类比的软件工作量估算的多目标特征选择方法[J].东南大学学报（英文版）,2018,34(3):295-302,8.基金项目
The National Natural Science Foundation of China (No.61602267,61202006),the Open Project of State Key Laboratory for Novel Software Technology at Nanjing University (No.KFKT2016B18). （No.61602267,61202006）
