Dataset Diversity for Metamorphic Testing of Machine Learning Software

Author:

Nakajima Shin

Publisher

Springer International Publishing

Reference23 articles.

1. Ammann, P., Knight, J.C.: Data diversity: an approach to software fault tolerance. IEEE TC 37(4), 418–425 (1988)

2. Ammann, P., Offutt, J.: Introduction to Software Testing. Cambridge University Press, Cambridge (2008)

3. Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Boston (2006). https://doi.org/10.1007/978-1-4615-7566-5

4. Brinker, K.: Incorporating diversity in active learning with support vector machines. In: Proceedings of 20th ICML, pp. 59–66 (2003)

5. Chen, T.Y., Cheung, S.C., Yiu, S.M.: Metamorphic testing - a new approach for generating next test cases. HKUST-CS98-01, The Hong Kong University of Science and Technology (1998)

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