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This paper presents the first exact and certified algorithms for computing Data Shapley values in weighted k-nearest-neighbor regression and soft-label prediction, closing a known gap in the literature. It provides a pseudo-polynomial-time exact algorithm, a certified FPTAS, and an open-source library, with empirical validation of exactness and the limitations of Monte-Carlo approximation.