The goal of discriminant analysis is to obtain rules that describe the separation between groups of observations. Moreover it allows to classify new observations into one of the k...
We propose a feature selection method that constructs each new feature by analysis of tight error clusters. This is a greedy, time-efficient forward selection algorithm that itera...
Abstract. We address the problem of comparing sets of images for object recognition, where the sets may represent arbitrary variations in an object's appearance due to changin...
An improved method for generalized constrained canonical correlation analysis (GCCANO) is proposed. In the original GCCANO, data matrices were first decomposed into the sum of sev...
The availability of high density single nucleotide polymorphisms (SNPs) data has made genome-wide association study computationally challenging. Twolocus epistasis (gene-gene inter...