Software Defect Prediction Based on Fuzzy Cost Broad Learning System

被引:0
作者
Cao, Heling [1 ,2 ,3 ,4 ]
Cui, Zhiying [1 ,2 ,3 ,4 ]
Chu, Yonghe [1 ,2 ,3 ,4 ]
Gong, Lina [5 ]
Liu, Guangen [1 ,2 ,3 ,4 ]
Wang, Yun [1 ,2 ,3 ,4 ]
Tian, Fangchao [1 ,2 ,3 ,4 ]
Li, Peng [4 ]
Ge, Haoyang [1 ,2 ,3 ,4 ]
机构
[1] Henan Univ Technol, Key Lab Grain Informat Proc & Control, Minist Educ, Zhengzhou, Peoples R China
[2] Henan Univ Technol, Henan Key Lab Grain Photoelect Detect & Control, Zhengzhou, Peoples R China
[3] Henan Univ Technol, Coll Informat Sci & Engn, Zhengzhou, Peoples R China
[4] Henan Univ Technol, Ctr Complex Sci, Zhengzhou, Peoples R China
[5] Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing, Peoples R China
关键词
broad learning system; cost matrix; feature space; fuzzy membership functions; software defect prediction; NEURAL-NETWORKS;
D O I
10.1155/int/6463038
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Software defect prediction (SDP) is an effective approach to ensure software reliability. Machine learning models have been widely employed in SDP, but they ignore the impact of class imbalance, noise and outliers on the prediction performance. This study proposes a fuzzy cost broad learning system (FC-BLS). FC-BLS not only handles class imbalance problems but also considers the specific sample distribution to address noise and outliers in software defect datasets. Our approach draws fully on the idea of the cost matrix and fuzzy membership functions. It introduces them to BLS, where the cost matrix prioritises the training errors on the minority samples. Hence, the classification hyperplane position is more reasonable, and fuzzy membership functions calculate the membership degree of the sample in a feature mapping space to remove the prediction error caused by noise and outlier samples. Then, the optimisation problem is constructed based on the idea that the minority class and normal instances have relatively high costs. By contrast, the majority class and noise and outlier instances have relatively small costs. This study conducted experiments on nine NASA SDP datasets, and the experimental findings demonstrated the effectiveness of the proposed methodology on most datasets.
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页数:13
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