Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using the Dual of Proximity Graphs for Binary Decision Tree Design
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
Simple termination conditions for k-nearest neighbor method
Pattern Recognition Letters
Data mining tasks and methods: Classification: nearest-neighbor approaches
Handbook of data mining and knowledge discovery
BWT-based efficient shape matching
Proceedings of the 2007 ACM symposium on Applied computing
New Algorithms for Efficient High-Dimensional Nonparametric Classification
The Journal of Machine Learning Research
Fast k most similar neighbor classifier for mixed data (tree k-MSN)
Pattern Recognition
Probably correct k-nearest neighbor search in high dimensions
Pattern Recognition
Improving the speed and stability of the k-nearest neighbors method
Pattern Recognition Letters
Hi-index | 0.14 |
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.