A Comparison of Semi-Supervised Classification Approaches for Software Defect Prediction

A Comparison of Semi-Supervised Classification Approaches for Software Defect Prediction

Predicting the defect-prone modules when the previous defect labels of modules are limited is a challenging problem encountered in the software industry. Supervised classification approaches cannot build high-performance prediction models with few defect data, leading to the need for new methods, te...

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Bibliographic Details
Main Author: Catal Cagatay
Format: Article
Language:English
Published: De Gruyter 2014-01-01
Series:Journal of Intelligent Systems
Subjects:
defect prediction
expectation-maximization
low-density separation
quality estimation
semi-supervised classification
support vector machines
Online Access:https://doi.org/10.1515/jisys-2013-0030

Internet

https://doi.org/10.1515/jisys-2013-0030

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