— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
Abstract. Training data as well as supplementary data such as usagebased click behavior may abound in one search market (i.e., a particular region, domain, or language) and be much...
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
This paper presents a method for selection of SIFT(Scale-Invariant Feature Transform) feature points using OC-SVM (One Class-Support Vector Machines). We proposed the method for au...
Abstract. This paper presents a new feature selection method and an outliers detection algorithm. The presented method is based on using a genetic algorithm combined with a problem...