Multiple kernel ensemble learning for software defect prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Software
Link
http://link.springer.com/content/pdf/10.1007/s10515-015-0179-1.pdf
Reference62 articles.
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3. Bennett, K.P., Momma, M., Embrechts, M.J.: MARK: a boosting algorithm for heterogeneous kernel models. In: Proceedings of 8th ACM-SIGKDD International Conference on Knowledge Discovery and Data Mining, Edmonton, Canada: ACM, pp. 24–31 (2002)
4. Bezerra, E. Miguel, Oliveiray, A.L.I., Adeodatoz, P.J.L.: Predicting software defects: a cost-sensitive approach. International Conference Systems, Man, and Cybernetics, pp. 2515–2522 (2011)
5. Bi, J., Zhang, T., Bennett, K.P.: Column-generation boosting methods for mixture of kernels. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, USA: ACM, pp. 521–526 (2004)
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