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]
@inproceedings{MartinANB18,
title = {Upsilon-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects},
author = {Cuauhtémoc López Martín and Mohammad Azzeh and Ali Bou Nassif and Shadi Banitaan},
year = {2018},
doi = {10.1109/ICMLA.2018.00224},
url = {https://doi.org/10.1109/ICMLA.2018.00224},
researchr = {https://researchr.org/publication/MartinANB18},
cites = {0},
citedby = {0},
pages = {1377-1382},
booktitle = {17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018, Orlando, FL, USA, December 17-20, 2018},
editor = {M. Arif Wani and Mehmed Kantardzic and Moamar Sayed Mouchaweh and João Gama and Edwin Lughofer},
publisher = {IEEE},
isbn = {978-1-5386-6805-4},
}