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Toward Comprehensible Software Fault Prediction Models Using Bayesian Network Classifiers
Found in: IEEE Transactions on Software Engineering
By Karel Dejaeger,Thomas Verbraken,Bart Baesens
Issue Date:February 2013
pp. 237-257
Software testing is a crucial activity during software development and fault prediction models assist practitioners herein by providing an upfront identification of faulty software code by drawing upon the machine learning literature. While especially the ...
 
Data Mining Techniques for Software Effort Estimation: A Comparative Study
Found in: IEEE Transactions on Software Engineering
By Karel Dejaeger,Wouter Verbeke,David Martens,Bart Baesens
Issue Date:March 2012
pp. 375-397
A predictive model is required to be accurate and comprehensible in order to inspire confidence in a business setting. Both aspects have been assessed in a software effort estimation setting by previous studies. However, no univocal conclusion as to which ...
 
Software Effort Prediction Using Regression Rule Extraction from Neural Networks
Found in: Tools with Artificial Intelligence, IEEE International Conference on
By Rudy Setiono, Karel Dejaeger, Wouter Verbeke, David Martens, Bart Baesens
Issue Date:October 2010
pp. 45-52
Neural networks are often selected as tool for software effort prediction because of their capability to approximate any continuous function with arbitrary accuracy. A major drawback of neural networks is the complex mapping between inputs and output, whic...
 
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