GBKNN replaces fixed k with a neighborhood size derived from the nearest granular ball and uses a Fisher criterion to guide ball splitting, reporting higher accuracy and speed than 13 KNN baselines on 12 datasets.
Intelligent handwritten recognition using hybrid cnn architectures based-svm classifier with dropout,
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Adaptive $k$ Nearest Neighbors Classifier via Granular Ball Computing
GBKNN replaces fixed k with a neighborhood size derived from the nearest granular ball and uses a Fisher criterion to guide ball splitting, reporting higher accuracy and speed than 13 KNN baselines on 12 datasets.