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» Feature selection in a kernel space
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IJCNN
2008
IEEE
14 years 1 months ago
Feature selection based on kernel discriminant analysis for multi-class problems
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
Tsuneyoshi Ishii, Shigeo Abe
ICASSP
2011
IEEE
12 years 11 months ago
Feature selection based on Multiple Kernel Learning for single-channel sound source localization using the acoustic transfer fun
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work [1], we discussed the single-channel sound source localization...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
SLSFS
2005
Springer
14 years 29 days ago
Random Projection, Margins, Kernels, and Feature-Selection
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
Avrim Blum
ECCV
2004
Springer
14 years 9 months ago
Kernel Feature Selection with Side Data Using a Spectral Approach
Abstract. We address the problem of selecting a subset of the most relevant features from a set of sample data in cases where there are multiple (equally reasonable) solutions. In ...
Amnon Shashua, Lior Wolf
ICISP
2010
Springer
14 years 8 days ago
Classification of High-Resolution NMR Spectra Based on Complex Wavelet Domain Feature Selection and Kernel-Induced Random Forest
High-resolution nuclear magnetic resonance (NMR) spectra contain important biomarkers that have potentials for early diagnosis of disease and subsequent monitoring of its progressi...
Guangzhe Fan, Zhou Wang, Seoung Bum Kim, Chivalai ...