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SADM
2010
196views more  SADM 2010»
13 years 2 months ago
Bayesian adaptive nearest neighbor
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...
Ruixin Guo, Sounak Chakraborty
ICPR
2006
IEEE
14 years 8 months ago
Automatic Adjustment of Discriminant Adaptive Nearest Neighbor
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...
Cédric Archambeau, Michel Verleysen, Nicola...
ADBIS
2007
Springer
256views Database» more  ADBIS 2007»
13 years 11 months ago
Adaptive k-Nearest-Neighbor Classification Using a Dynamic Number of Nearest Neighbors
Classification based on k-nearest neighbors (kNN classification) is one of the most widely used classification methods. The number k of nearest neighbors used for achieving a high ...
Stefanos Ougiaroglou, Alexandros Nanopoulos, Apost...
FSKD
2006
Springer
147views Fuzzy Logic» more  FSKD 2006»
13 years 11 months ago
Adaptive Nearest Neighbor Classifier Based on Supervised Ellipsoid Clustering
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...
ICPR
2002
IEEE
14 years 8 months ago
Adaptive Kernel Metric Nearest Neighbor Classification
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to the curse-ofdimensionality. Sev...
Jing Peng, Douglas R. Heisterkamp, H. K. Dai