mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - Information Sciences, 2011 - Elsevier
This paper presents a hybrid filter–wrapper feature subset selection algorithm based on
particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter …
被引用次数：367 相关文章
[PDF] psu.edu

[PDF][PDF] mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - Information Sciences, 2011 - Citeseer
abstract This paper presents a hybrid filter–wrapper feature subset selection algorithm
based on particle swarm optimization (PSO) for support vector machine (SVM) classification …

mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - Information Sciences—Informatics and …, 2011 - dl.acm.org
This paper presents a hybrid filter-wrapper feature subset selection algorithm based on
particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter …

mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - Information Sciences, 2011 - infona.pl
This paper presents a hybrid filter–wrapper feature subset selection algorithm based on
particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter …
[PDF] academia.edu

[PDF][PDF] mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - Information Sciences, 2011 - academia.edu
abstract This paper presents a hybrid filter–wrapper feature subset selection algorithm
based on particle swarm optimization (PSO) for support vector machine (SVM) classification …
[PDF] researchgate.net

[PDF][PDF] mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - Information Sciences, 2011 - researchgate.net
abstract This paper presents a hybrid filter–wrapper feature subset selection algorithm
based on particle swarm optimization (PSO) for support vector machine (SVM) classification …

mr (2) PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - 2011 - aperta.ulakbim.gov.tr
This paper presents a hybrid filter-wrapper feature subset selection algorithm based on
particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter …

mr (2) PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - 2011 - aperta.ulakbim.gov.tr
This paper presents a hybrid filter-wrapper feature subset selection algorithm based on
particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter …
[PDF] academia.edu

[PDF][PDF] mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

A Unler, A Murat, RB Chinnam - Information Sciences, 2011 - academia.edu
abstract This paper presents a hybrid filter–wrapper feature subset selection algorithm
based on particle swarm optimization (PSO) for support vector machine (SVM) classification …