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» Memetic Algorithms for Feature Selection on Microarray Data
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WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
14 years 29 days ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
ICCV
2001
IEEE
14 years 9 months ago
Feature Selection from Huge Feature Sets
The number of features that can be computed over an image is, for practical purposes, limitless. Unfortunately, the number of features that can be computed and exploited by most c...
José Bins, Bruce A. Draper
AUSAI
2006
Springer
13 years 9 months ago
An Efficient Alternative to SVM Based Recursive Feature Elimination with Applications in Natural Language Processing and Bioinfo
The SVM based Recursive Feature Elimination (RFE-SVM) algorithm is a popular technique for feature selection, used in natural language processing and bioinformatics. Recently it wa...
Justin Bedo, Conrad Sanderson, Adam Kowalczyk
GECCO
2003
Springer
191views Optimization» more  GECCO 2003»
14 years 22 days ago
Artificial Immune System for Classification of Gene Expression Data
DNA microarray experiments generate thousands of gene expression measurement simultaneously. Analyzing the difference of gene expression in cell and tissue samples is useful in dia...
Shin Ando, Hitoshi Iba
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
Robust imputation method for missing values in microarray data
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
Dankyu Yoon, Eun-Kyung Lee, Taesung Park