Sciweavers

PR
2008
93views more  PR 2008»
13 years 11 months ago
Genetic algorithm-based feature set partitioning for classification problems
Feature set partitioning generalizes the task of feature selection by partitioning the feature set into subsets of features that are collectively useful, rather than by finding a ...
Lior Rokach
JMLR
2006
85views more  JMLR 2006»
13 years 11 months ago
Streamwise Feature Selection
In streamwise feature selection, new features are sequentially considered for addition to a predictive model. When the space of potential features is large, streamwise feature sel...
Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H...
JUCS
2008
159views more  JUCS 2008»
13 years 11 months ago
Two Step Swarm Intelligence to Solve the Feature Selection Problem
: In this paper we propose a new approach to Swarm Intelligence called Two-Step Swarm Intelligence. The basic idea is to split the heuristic search performed by agents into two sta...
Yudel Gómez, Rafael Bello, Amilkar Puris, M...
JUCS
2008
130views more  JUCS 2008»
13 years 11 months ago
Feature Selection for the Classification of Large Document Collections
: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of...
Janez Brank, Dunja Mladenic, Marko Grobelnik, Nata...
JCP
2006
85views more  JCP 2006»
13 years 11 months ago
A Constructive Meta-Level Feature Selection Method based on Method Repositories
Feature selection is one of key issues related with data pre-processing of classification task in a data mining process. Although many efforts have been done to improve typical fea...
Hidenao Abe, Takahira Yamaguchi
JMM2
2008
124views more  JMM2 2008»
13 years 11 months ago
Integrated Feature Selection and Clustering for Taxonomic Problems within Fish Species Complexes
As computer and database technologies advance rapidly, biologists all over the world can share biologically meaningful data from images of specimens and use the data to classify th...
Huimin Chen, Henry L. Bart Jr., Shuqing Huang
IMDS
2006
33views more  IMDS 2006»
13 years 11 months ago
Operations strategy and flexibility: modeling with Bayesian classifiers
Purpose
María M. Abad-Grau, Daniel Arias-Aranda
BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 11 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 11 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
BMCBI
2008
160views more  BMCBI 2008»
13 years 11 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...