Feature selection is an important issue for object detection. In this paper, we propose an effective wrapper-based feature selection scheme using Binary Particle Swarm Optimizatio...
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Abstract. Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all cluste...
Marcelo N. Ribeiro, Manoel J. R. Neto, Ricardo Bas...
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...
In this paper, we adress the question of decoding cognitive information from functional Magnetic Resonance (MR) images using classification techniques. The main bottleneck for acc...