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F. Setoudehtanzangi

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#machine learning Preprint Sep 2026

Large Classification-Risk-Optional Label Acquisition

The adaptive classification-risk design attains lower mean error than this Fisher comparator across the labeling budgets considered, although it does not uniformly outperform entropy or margin sampling and differences among the targeted strategies become small as the labeling budget increases.

F. Setoudehtanzangi, Geoffrey J. McLachlan · 0 citations

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