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Efficient Local Flexible Nearest Neighbor Classification
[chapter]
2002
Proceedings of the 2002 SIAM International Conference on Data Mining
The nearest neighbor technique is a simple and appealing method to address classification problems. It relies on the assumption of locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with a finite number of examples due to the curse of dimensionality. Severe bias can be introduced under these conditions when using the nearest neighbor rule. The employment of a local adaptive metric becomes crucial in order to keep class conditional probabilities
doi:10.1137/1.9781611972726.21
dblp:conf/sdm/DomeniconiG02
fatcat:vq2sczslajgmjhtujtvbo7ugfy