40 search results - page 2 / 8 » Feature Selection via Concave Minimization and Support Vecto... |
ICDM
2007
IEEE
13 years 7 months ago
2007
IEEE
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
IWANN
2009
Springer
13 years 11 months ago
2009
Springer
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
INFORMS
1998
13 years 5 months ago
1998
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
FLAIRS
2001
13 years 6 months ago
2001
Theoretically well-founded, Support Vector Machines (SVM)are well-knownto be suited for efficiently solving classification problems. Althoughimprovedgeneralization is the maingoal...
ICML
2005
IEEE
14 years 6 months ago
2005
IEEE
In this paper we describe a new method to reduce the complexity of support vector machines by reducing the number of necessary support vectors included in their solutions. The red...