Best when Data density is irregular Domain-meaningful distance threshold exists KNN is preferable when data density varies across the feature space, and when a fixed, predictable neighborhood is ...

Abstract: The traditional K-Nearest Neighbor (KNN) algorithm often encounters problems such as weak feature expression ability and poor adaptability to fixed K-values in image classification tasks, ...

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...