JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (1): 15-21.doi: 10.6040/j.issn.1672-3961.0.2016.304

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Random undersampling and POSS method for software defect prediction

FANG Hao, LI Yun*   

  1. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, Jiangsu, China
  • Received:2016-07-22 Online:2017-02-20 Published:2016-07-22

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Abstract: In order to solve the problem of imbalance distribution in software defect prediction, POSS(pareto optimization for subset selection)feature selection and random undersampling was applied in this paper, and SVM was used to build the prediction model. The experimental results showed that the problem could be solved effectively by using multiple random undersampling, and the POSS method was treated subset selection as a bi-objective optimization, which could improve the accuracy of classification, the effectiveness of proposed method was verified by comparing with Relief、Fisher、MI(mutual information).

Key words: class imbalance, data sampling, feature selection, software defect prediction

CLC Number: 

  • TP391
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