Support vector machines with piecewise linear feature mapping

Feature Selection Using Linear Support Vector Machines

Linear Penalization Support Vector Machines for Feature Selection

We propose a linearly penalized support vector machines (LP-SVM) model for feature selection. Its application to a problem of customer retention and a comparison with other feature selection techniques underlines its effectiveness.

Feature selection combining linear support vector machines and concave optimization

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Linear programming support vector machines

Based on the analysis of the conclusions in the statistical learning theory, especially the VC dimension of linear functions, linear programming support vector machines (or SVMs) are presented including linear programming linear and nonlinear SVMs. In linear programming SVMs, in order to improve the speed of the training time, the bound of the VC dimension is loosened properly. Simulation resul...

Locally Linear Support Vector Machines

Linear support vector machines (svms) have become popular for solving classification tasks due to their fast and simple online application to large scale data sets. However, many problems are not linearly separable. For these problems kernel-based svms are often used, but unlike their linear variant they suffer from various drawbacks in terms of computational and memory efficiency. Their respon...