Motivated by support vector classifiers (SVCs), we propose in this paper a novel family of classifiers, called kernel-based Wilcoxon classifiers (KWCs), for ...

This paper proposes a novel family of classifiers, called kernel-based Wilcoxon classifiers (KWCs), for nonlinear classification problems, which has the ...

Abstract—Nonparametric Wilcoxon regressors, which generalize the rank-based Wilcoxon approach for linear parametric regression problems to nonparametric ...

Study on kernel-based Wilcoxon classifiers. November 2010. DOI:10.1109/ISKE.2010.5680870. Authors: Hsu Kun Wu at National Sun Yat-sen University · Hsu Kun Wu.

The Wilcoxon signed rank test was proposed as a simple, yet powerful hypothesis test for the symmetry of a distribution about a known median or for testing the ...

A growing number of studies has shown that machine learning classifiers can be used to extract exciting new information from neuroimaging data.

In this paper, we present a new gene selection method based on clustering, in which dissimilarity measures are obtained through kernel functions.

KBN based classifiers require more storage space and have more computational cost than CGN based classifiers for learn- ing and classifying new instances.

This paper reviews and extends the field of similarity-based classification, presenting new analy- ses, algorithms, data sets, and a comprehensive set of ...

Abstract. Objective. The purpose of this project was to determine whether machine-learning classifiers could predict which patients would require a preoper.