Kernel Based Asymmetric Learning for Software Defect Prediction

Ying MA; Guangchun LUO; Hao CHEN

doi:10.1587/transinf.E95.D.267

IEICE Transactions on Information and Systems

Online ISSN : 1745-1361
Print ISSN : 0916-8532

Regular Section

Kernel Based Asymmetric Learning for Software Defect Prediction

Ying MA, Guangchun LUO, Hao CHEN

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Keywords: defect prediction, class imbalance, kernel principal component analysis, machine learning

JOURNAL FREE ACCESS

2012 Volume E95.D Issue 1 Pages 267-270

DOI https://doi.org/10.1587/transinf.E95.D.267

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Abstract

A kernel based asymmetric learning method is developed for software defect prediction. This method improves the performance of the predictor on class imbalanced data, since it is based on kernel principal component analysis. An experiment validates its effectiveness.

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