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» A New Indexing Method for High Dimensional Dataset
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157
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ADBIS
2007
Springer
256views Database» more  ADBIS 2007»
15 years 4 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...
90
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ICML
2010
IEEE
15 years 1 months ago
Improved Local Coordinate Coding using Local Tangents
Local Coordinate Coding (LCC), introduced in (Yu et al., 2009), is a high dimensional nonlinear learning method that explicitly takes advantage of the geometric structure of the d...
Kai Yu, Tong Zhang
87
Voted
WWW
2002
ACM
16 years 1 months ago
Searching with numbers
A large fraction of the useful web comprises of specification documents that largely consist of hattribute name, numeric valuei pairs embedded in text. Examples include product in...
Rakesh Agrawal, Ramakrishnan Srikant
98
Voted
ICML
2007
IEEE
16 years 1 months ago
Minimum reference set based feature selection for small sample classifications
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...
Xue-wen Chen, Jong Cheol Jeong
128
Voted
CCIA
2005
Springer
15 years 2 months ago
Feature Selection and Outliers Detection with Genetic Algorithms and Neural Networks
Abstract. This paper presents a new feature selection method and an outliers detection algorithm. The presented method is based on using a genetic algorithm combined with a problem...
Agusti Solanas, Enrique Romero, Sergio Góme...