In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
Given the spectral difference between speech and acoustic events, we propose using Kullback-Leibler distance to quantify the discriminant capability of all speech feature componen...
Xi Zhou, Xiaodan Zhuang, Ming Liu, Hao Tang, Mark ...
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...
Abstract--This study presents a computer-aided diagnosis system using sequential forward floating selection (SFFS) with support vector machine (SVM) to diagnose gastric histology o...