QGB-W$k$NN: Quantum Granular-Ball Learning for Robust Classification
An efficient and reliable weighted $K$-nearest neighbor classification framework based on quantum granular balls, termed QGB-W$k$NN is proposed, suggesting that reliability-aware quantum granular-ball learning provides a promising paradigm for efficient and robust nearest-neighbor classification.
Su-Zhen Yuan, De-Hang Chen, Li-Feng Shen et al.
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