107 citations · 107 across the 1 of their papers we have counts for
3 papers
cs.SE2020★ 107 cited
Assessing Software Defection Prediction Performance: Why Using the Matthews Correlation Coefficient Matters
Jingxiu Yao, Martin Shepperd
Context: There is considerable diversity in the range and design of computational experiments to assess classifiers for software defect prediction. This is particularly so, regardi…
cs.LG2019
The Prevalence of Errors in Machine Learning Experiments
Martin Shepperd, Yuchen Guo, Ning Li +7
Context: Conducting experiments is central to research machine learning research to benchmark, evaluate and compare learning algorithms. Consequently it is important we conduct rel…
cs.SE2019
A Systematic Review of Unsupervised Learning Techniques for Software Defect Prediction
Ning Li, Martin Shepperd, Yuchen Guo
Background: Unsupervised machine learners have been increasingly applied to software defect prediction. It is an approach that may be valuable for software practitioners because it…