Sciweavers

1253 search results - page 18 / 251
» Feature selection for linear support vector machines
Sort
View
ICML
2004
IEEE
14 years 8 months ago
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
Evgeniy Gabrilovich, Shaul Markovitch
ML
2002
ACM
180views Machine Learning» more  ML 2002»
13 years 7 months ago
Gene Selection for Cancer Classification using Support Vector Machines
Isabelle Guyon, Jason Weston, Stephen Barnhill, Vl...
JMLR
2008
110views more  JMLR 2008»
13 years 7 months ago
A Bahadur Representation of the Linear Support Vector Machine
The support vector machine has been successful in a variety of applications. Also on the theoretical front, statistical properties of the support vector machine have been studied ...
Ja-Yong Koo, Yoonkyung Lee, Yuwon Kim, Changyi Par...
ICML
2010
IEEE
13 years 8 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
ICMLA
2010
13 years 5 months ago
A New Approach to Classification with the Least Number of Features
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separati...
Sascha Klement, Thomas Martinetz