Using Class Imbalance Learning for Software Defect Prediction

To facilitate software testing, and save testing costs, a wide range of machine learning methods have been studied to predict defects in software modules. Unfortunately, the imbalanced nature of this type of data increases the learning difficulty of such a task. Class imbalance learning specializes...

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Veröffentlicht in:	IEEE transactions on reliability Jg. 62; H. 2; S. 434 - 443
Hauptverfasser:	Shuo Wang, Xin Yao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.06.2013
Schlagworte:	Class imbalance learning ensemble learning Learning systems Measurement negative correlation learning Niobium Prediction algorithms Software Software algorithms software defect prediction Training
ISSN:	0018-9529, 1558-1721
Online-Zugang:	Volltext
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