Testing the Robustness of Machine Learning Models Through Mutations
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-70248-8_24
Reference30 articles.
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3. Breiman, L.: Random forests. Mach. Learn. 45, 5–32 (2001)
4. Brito, C., Durelli, V.H.S., Durelli, R.S., de Souza, S.R.S., Vincenzi, A.M.R., Delamaro, M.E.: A preliminary investigation into using machine learning algorithms to identify minimal and equivalent mutants. In: 2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), pp. 304–313 (2020)
5. Chen, T.Y., et al.: Metamorphic testing: a review of challenges and opportunities. ACM Comput. Surv. 51(1) (2018)
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