Springer Verlag (Germany), IFIP Advances in Information and Communication Technology , p. 327-336, 2012
DOI: 10.1007/978-3-642-33409-2_34
Full text: Download
This paper proposes a hybrid method for fast and accurate Nearest Neighbor Classification. The method consists of a non-parametric cluster-based algorithm that produces a two-level speed-up data structure and a hybrid algorithm that accesses this structure to perform the classification. The proposed method was evaluated using eight real-life datasets and compared to four known speed-up methods. Experimental results show that the proposed method is fast and accurate, and, in addition, has low pre-processing computational cost.