Nearest neighbor classifier is a widely-used effective method for multi-class problems. However, it suffers from the problem of the curse of dimensionality in high dimensional spac...
Guo-Jun Zhang, Ji-Xiang Du, De-Shuang Huang, Tat-M...
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to the curse-ofdimensionality. Sev...
K-Nearest Neighbors relies on the definition of a global metric. In contrast, Discriminant Adaptive Nearest Neighbor (DANN) computes a different metric at each query point based o...