One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
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 ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
In this paper, a multi-class feature selection scheme based on recursive feature elimination (RFE) is proposed for texture classifications. The feature selection scheme is perform...
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...