An attribute weight setting method for k -NN based binary classification using quadratic programming
Lu Zhang, Frans Coenen, Paul H. Leng · 2002
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. 1.