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In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advantage over the standard. 2-norm SVM, especially when there are ...
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In this paper, we consider the 1-norm SVM. We class classi£cation. argue that the 1-norm SVM may have some advantage over the standard 2-norm SVM.
We argue that the 1-norm SVM may have some advantage over the standard 2-norm SVM, especially when there are redundant noise features. We also propose an ...
Abstract—In this paper, we introduce a new general definition of L1-norm SVM (GL1-SVM) for feature selection and represent it as a polynomial mixed 0-1 ...
The standard L2-norm support vector machine (SVM) is a widely used tool for the classification problem. The L1-norm SVM is a variant of the standard L2-norm ...
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian,. 2000; Bradley and Mangasarian, 1998), are formulated here as a ...
Usually the 1-norm SVC works with parameters not being too large or too small; thus the 1-norm SVC has good generalization performance and the ESV bound is ...
In this paper, we introduce a new general definition of L1-norm SVM (GL1-SVM) for feature selection and represent it as a polynomial mixed 0-1 programming ...
In this article, we develop a new L1-norm multi-class SVM. (L1MSVM) and investigate its feasibility in classification and variable selection. In multi-class ...
It is argued that the 1-norm SVM may have some advantage over the standard 2- norm SVM, especially when there are redundant noise features, and an efficient ...