Title :
A fast algorithm for the nearest-neighbor classifier
Author :
Djouadi, Abdelhamid ; Bouktache, Essaid
Author_Institution :
Lucent Technol., Columbus, OH, USA
fDate :
3/1/1997 12:00:00 AM
Abstract :
A fast algorithm that finds the nearest neighbor (NN) of an unknown sample from a design set of labeled samples is proposed. This algorithm requires a quite moderate preprocessing effort and a rather excessive storage, but it accomplishes substantial computational savings during classification. The performance of the algorithm is described and compared to the performance of the conventional one. Results on simulated data are provided to illustrate the computational savings that may be achieved using this fast algorithm
Keywords :
computational complexity; pattern classification; computational savings; design set; fast algorithm; labeled samples; large storage requirement; nearest-neighbor classifier; preprocessing; Algorithm design and analysis; Classification algorithms; Classification tree analysis; Computational modeling; Density measurement; Nearest neighbor searches; Neural networks; Partitioning algorithms; Pattern recognition; Testing;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
