Bridging the gap between ML solutions and their business requirements using feature interactions

ESEC/SIGSOFT FSE, pp. 1048-1058, 2019.

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Abstract:

Machine Learning (ML) based solutions are becoming increasingly popular and pervasive. When testing such solutions, there is a tendency to focus on improving the ML metrics such as the F1-score and accuracy at the expense of ensuring business value and correctness by covering business requirements. In this work, we adapt test planning met...More

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