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» Support vector machine for functional data classification
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NIPS
2000
15 years 7 months ago
Feature Selection for SVMs
We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error. This sear...
Jason Weston, Sayan Mukherjee, Olivier Chapelle, M...
ICML
2007
IEEE
16 years 7 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
NN
2002
Springer
125views Neural Networks» more  NN 2002»
15 years 5 months ago
Generalized relevance learning vector quantization
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
Barbara Hammer, Thomas Villmann
ICIP
1998
IEEE
16 years 7 months ago
A Combinatorical Approach to Vector Tomography for Doppler Spectral Data
Velocity spectra of a flow can be made by ultrasound Doppler measurements. Using only part of the information in these spectra, it is possible to reconstruct the solenoid part and...
Kent Stråhlén
KDD
1998
ACM
112views Data Mining» more  KDD 1998»
15 years 10 months ago
Evaluating Usefulness for Dynamic Classification
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...