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ICANN
2010
Springer
14 years 7 months ago
The Support Feature Machine for Classifying with the Least Number of Features
We propose the so-called Support Feature Machine (SFM) as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separating hyperplan...
Sascha Klement, Thomas Martinetz
BMCBI
2008
169views more  BMCBI 2008»
14 years 10 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
JMLR
2008
123views more  JMLR 2008»
14 years 9 months ago
Optimization Techniques for Semi-Supervised Support Vector Machines
Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs...
Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keer...
COLING
2002
14 years 9 months ago
Extracting Important Sentences with Support Vector Machines
Extracting sentences that contain important information from a document is a form of text summarization. The technique is the key to the automatic generation of summaries similar ...
Tsutomu Hirao, Hideki Isozaki, Eisaku Maeda, Yuji ...
NN
2000
Springer
161views Neural Networks» more  NN 2000»
14 years 9 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys