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Building Useful Models from Imbalanced Data with Sampling and Boosting.

, , , and . FLAIRS, page 306-311. AAAI Press, (2008)

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Which Software Modules have Faults which will be Discovered by Customers?, , , and . Journal of Software Maintenance, 11 (1): 1-18 (1999)An Empirical Study of the Classification Performance of Learners on Imbalanced and Noisy Software Quality Data., , , and . IRI, page 651-658. IEEE Systems, Man, and Cybernetics Society, (2007)Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data., and . IRI, page 630-637. IEEE Systems, Man, and Cybernetics Society, (2007)Uncertain Classification of Fault-Prone Software Modules., , , , and . Empirical Software Engineering, 7 (4): 295-295 (2002)Modelling software quality with GP., , , and . GECCO, page 1232. Morgan Kaufmann, (1999)Software quality modeling: The impact of class noise on the random forest classifier., , , and . IEEE Congress on Evolutionary Computation, page 3853-3859. IEEE, (2008)Stability and Classification Performance of Feature Selection Techniques., , and . ICMLA (1), page 151-156. IEEE Computer Society, (2011)The Dimensionality of Program Complexity., and . ICSE, page 245-253. IEEE Computer Society / ACM Press, (1989)Software Defect Prediction for High-Dimensional and Class-Imbalanced Data., and . SEKE, page 89-94. Knowledge Systems Institute Graduate School, (2011)Learning from Software Quality Data with Class Imbalance and Noise., , , and . SEKE, page 487-. Knowledge Systems Institute Graduate School, (2007)