A Machine Learning Model Comparison and Selection Framework for Software Defect Prediction Using VIKOR-Reference-Cited by-同舟云学术

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A Machine Learning Model Comparison and Selection Framework for Software Defect Prediction Using VIKOR

Published:2021-09-10 Issue: Volume: Page:890-898
ISSN:2367-3370
Container-title:Human Interaction, Emerging Technologies and Future Systems V
language:
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Author:

Martinez Miguel Ángel Quiroz,Tayupanda Byron Alcívar Martínez,Paguay Sulay Stephanie Camatón,Peñafiel Luis Andy Briones

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-85540-6_113

Reference20 articles.

1. Yang, J., Qian, H.: Defect prediction on unlabeled datasets by using unsupervised clustering. In: Proceedings of the 18th IEEE Conference on High Performance Computing and Communications; 14th IEEE International Conference on Smart City; 2nd International Conference on Data Science and Systems, pp. 465–472 (2017)

2. Ferenc, R., Gyimesi, P., Gyimesi, G., Tóth, Z., Gyimóthy, T.: An automatically created novel bug dataset and its validation in bug prediction. J. Syst. Softw. 169, 110691 (2020)

3. Çatal, Ç.: The use of cross-company fault data for the software fault prediction problem. Turkish J. Electr. Eng. Comput. Sci. 24, 3714–3723 (2016)

4. Shanthini, A.: Software metrics for fault prediction using machine learning approaches. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2, 274–278 (2012)

5. Gao, Y., Yang, C.: Software defect prediction based on manifold learning in subspace selection. In: ACM International Conference Proceedings Series (2016)

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