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» Feature selection in a kernel space
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ICML
2001
IEEE
14 years 10 months ago
Feature selection for high-dimensional genomic microarray data
We report on the successful application of feature selection methods to a classification problem in molecular biology involving only 72 data points in a 7130 dimensional space. Ou...
Eric P. Xing, Michael I. Jordan, Richard M. Karp
ICASSP
2010
IEEE
13 years 10 months ago
A kernel mean matching approach for environment mismatch compensation in speech recognition
The mismatch between training and test environmental conditions presents a challenge to speech recognition systems. In this paper, we investigate an approach for matching the dist...
Abhishek Kumar, John H. L. Hansen
SEBD
2008
177views Database» more  SEBD 2008»
13 years 11 months ago
Using PageRank in Feature Selection
Abstract. Feature selection is an important task in data mining because it allows to reduce the data dimensionality and eliminates the noisy variables. Traditionally, feature selec...
Dino Ienco, Rosa Meo, Marco Botta
ICMCS
2006
IEEE
105views Multimedia» more  ICMCS 2006»
14 years 4 months ago
Entropy and Memory Constrained Vector Quantization with Separability Based Feature Selection
An iterative model selection algorithm is proposed. The algorithm seeks relevant features and an optimal number of codewords (or codebook size) as part of the optimization. We use...
Sangho Yoon, Robert M. Gray
PAMI
2007
102views more  PAMI 2007»
13 years 9 months ago
Feature Subset Selection and Ranking for Data Dimensionality Reduction
—A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one ...
Hua-Liang Wei, Stephen A. Billings