Feature points for image correspondence are often selected according to subjective criteria (e.g. edge density, nostrils). In this paper, we present a general, non-subjective crit...
In rough set theory, the problem of feature selection aims to retain the discriminatory power of original features. Many feature selection algorithms have been proposed, however, q...
A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the c...
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
Feature selection is a data preprocessing step for classi cation and data mining tasks. Traditionally, feature selection is done by selecting a minimum number of features that det...