An Attribute Weight Setting Method for k-NN Based Binary Classification using Quadratic Programming

1 The authors are with the Department of Computer Science, the University of Liverpool, Liverpool L69 3BX, UK, emails: {lzhang, frans, phl}@csc.liv.ac.uk. Abstract. In this paper, we propose a new attribute weight setting method for k-NN based classifiers using quadratic programming, which is particular suitable for binary classification problems. Our method formalises the attribute weight setting problem as a quadratic programming problem and exploits commercial software to calculate attribute weights. Experiments show that our method is quite practical for various problems and can achieve a competitive performance. Another merit of the method is that it can use small training sets.