计算机应用研究2018，Vol.35Issue(2)：487-492,502,7.DOI:10.3969/j.issn.1001-3695.2018.02.036
面向软件缺陷个数预测的混合式特征选择方法
Hybrid feature selection method for number of software faults prediction
摘要
Abstract
Focused on the issue that the irrelevant and redundant features in software defect data would degrade the performance of the number of software faults prediction models,this paper proposed a hybrid feature selection method for the number of faults prediction(HFSNFP).Firstly,HFSNFP computed the relevance between every feature and the number of fault with ReliefT algorithm and selected the top m most relevant features.Then,HFSNFP grouped the m features with spectral clustering algorithm according to the correlation between every two features.Finally,HFSNFP selected the most relevant features from each resulted cluster to form the final feature subset using a wrapper search.Compared with the five existing filter-based feature selection methods,the experimental results show that HFSNFP increases PD value,reduces PF value and achieves better G-measure and RMSE values.Comparied with the two wrapper-based feature selection methods,it demonstrates that HFSNFP can achieve the high performance of the number of faults prediction and reduce the running time of feature selection.关键词
软件缺陷个数预测/特征选择/谱聚类/包裹式特征选择Key words
number of software faults prediction/feature selection/spectral clustering/wrapper-based feature selection分类
信息技术与安全科学引用本文复制引用
马子逸,马传香,刘瑞奇,余啸..面向软件缺陷个数预测的混合式特征选择方法[J].计算机应用研究,2018,35(2):487-492,502,7.基金项目
湖北大学精品课程(013665,150145) （013665,150145）
