Upsilon-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects - researchr publication authors

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Cuauhtémoc López Martín, Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan. Upsilon-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects. In M. Arif Wani, Mehmed Kantardzic, Moamar Sayed Mouchaweh, João Gama, Edwin Lughofer, editors, 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018, Orlando, FL, USA, December 17-20, 2018. pages 1377-1382, IEEE, 2018. [doi]

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