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ECAI
2010
Springer
13 years 6 months ago
Feature Selection by Approximating the Markov Blanket in a Kernel-Induced Space
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 ...
Qiang Lou, Zoran Obradovic
CLEAR
2007
Springer
179views Biometrics» more  CLEAR 2007»
14 years 3 months ago
HMM-Based Acoustic Event Detection with AdaBoost Feature Selection
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 ...
ICGA
1997
133views Optimization» more  ICGA 1997»
13 years 10 months ago
Messy Genetic Algorithms for Subset Feature Selection
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...
TITB
2008
136views more  TITB 2008»
13 years 9 months ago
Helicobacter Pylori-Related Gastric Histology Classification Using Support-Vector-Machine-Based Feature Selection
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...
Chun-Rong Huang, Pau-Choo Chung, Bor-Shyang Sheu, ...
ACL
2012
11 years 11 months ago
Joint Feature Selection in Distributed Stochastic Learning for Large-Scale Discriminative Training in SMT
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
Patrick Simianer, Stefan Riezler, Chris Dyer