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ICPR
2006
IEEE
11 years 4 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...
SADM
2010
196views more  SADM 2010»
9 years 9 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
PRL
2007
137views more  PRL 2007»
10 years 2 months ago
Improving nearest neighbor rule with a simple adaptive distance measure
The k-nearest neighbor rule is one of the simplest and most attractive pattern classification algorithms. However, it faces serious challenges when patterns of different classes...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
11 years 3 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal
BMCBI
2006
126views more  BMCBI 2006»
10 years 2 months ago
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Zizhen Yao, Walter L. Ruzzo
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