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Volumn 48, Issue 9, 2015, Pages 2798-2811

Relevance-redundancy feature selection based on ant colony optimization

Author keywords

Ant colony optimization; Curse of dimensionality; Feature selection; Filter model; Multivariate technique; Pattern recognition

Indexed keywords

ANT COLONY OPTIMIZATION; FEATURE EXTRACTION; PATTERN RECOGNITION; REDUNDANCY;

EID: 84929504035     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2015.03.020     Document Type: Article
Times cited : (173)

References (62)
  • 2
    • 17044405923 scopus 로고    scopus 로고
    • Toward integrating feature selection algorithms for classification and clustering
    • H. Liu, and L. Yu Toward integrating feature selection algorithms for classification and clustering IEEE Trans. Knowl. Data Eng. 17 2005 491 502
    • (2005) IEEE Trans. Knowl. Data Eng. , vol.17 , pp. 491-502
    • Liu, H.1    Yu, L.2
  • 3
    • 84861590173 scopus 로고    scopus 로고
    • An unsupervised approach to feature discretization and selection
    • A.J. Ferreira, and M.A.T. Figueiredo An unsupervised approach to feature discretization and selection Pattern Recognit. 45 2012 3048 3060
    • (2012) Pattern Recognit. , vol.45 , pp. 3048-3060
    • Ferreira, A.J.1    Figueiredo, M.A.T.2
  • 4
    • 68949155378 scopus 로고    scopus 로고
    • Feature subset selection in large dimensionality domains
    • I.A. Gheyas, and L.S. Smith Feature subset selection in large dimensionality domains Pattern Recognit. 43 2010 5 13
    • (2010) Pattern Recognit. , vol.43 , pp. 5-13
    • Gheyas, I.A.1    Smith, L.S.2
  • 5
    • 77956611003 scopus 로고    scopus 로고
    • Mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification
    • A. Unler, A. Murat, and R.B. Chinnam mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification Inf. Sci. 181 2011 4625 4641
    • (2011) Inf. Sci. , vol.181 , pp. 4625-4641
    • Unler, A.1    Murat, A.2    Chinnam, R.B.3
  • 6
    • 84900460549 scopus 로고    scopus 로고
    • An unsupervised feature selection algorithm based on ant colony optimization
    • S. Tabakhi, P. Moradi, and F. Akhlaghian An unsupervised feature selection algorithm based on ant colony optimization Eng. Appl. Artif. Intell. 32 2014 112 123
    • (2014) Eng. Appl. Artif. Intell. , vol.32 , pp. 112-123
    • Tabakhi, S.1    Moradi, P.2    Akhlaghian, F.3
  • 7
    • 80955181170 scopus 로고    scopus 로고
    • A two-stage feature selection method for text categorization by using information gain, principal component analysis and genetic algorithm
    • H. Uʇuz A two-stage feature selection method for text categorization by using information gain, principal component analysis and genetic algorithm Knowl.-Based Syst. 24 2011 1024 1032
    • (2011) Knowl.-Based Syst. , vol.24 , pp. 1024-1032
    • Uʇuz, H.1
  • 8
    • 79957440082 scopus 로고    scopus 로고
    • A new feature selection algorithm based on binomial hypothesis testing for spam filtering
    • J. Yang, Y. Liu, Z. Liu, X. Zhu, and X. Zhang A new feature selection algorithm based on binomial hypothesis testing for spam filtering Knowl.-Based Syst. 24 2011 904 914
    • (2011) Knowl.-Based Syst. , vol.24 , pp. 904-914
    • Yang, J.1    Liu, Y.2    Liu, Z.3    Zhu, X.4    Zhang, X.5
  • 9
    • 54249083003 scopus 로고    scopus 로고
    • An improved feature selection method based on ant colony optimization (ACO) evaluated on face recognition system
    • H.R. Kanan, and K. Faez An improved feature selection method based on ant colony optimization (ACO) evaluated on face recognition system Appl. Math. Comput. 205 2008 716 725
    • (2008) Appl. Math. Comput. , vol.205 , pp. 716-725
    • Kanan, H.R.1    Faez, K.2
  • 10
    • 35048837706 scopus 로고    scopus 로고
    • Ant colony optimization for feature selection in face recognition
    • David Zhang, Anil K. Jain (Eds.) Springer, Berlin, Heidelberg
    • Z. Yan, C. Yuan, Ant colony optimization for feature selection in face recognition, in: David Zhang, Anil K. Jain (Eds.) Biometric Authentication, Springer, Berlin, Heidelberg, 2004, pp. 221-226.
    • (2004) Biometric Authentication , pp. 221-226
    • Yan, Z.1    Yuan, C.2
  • 12
    • 35748932917 scopus 로고    scopus 로고
    • A review of feature selection techniques in bioinformatics
    • Y. Saeys, I. Inza, and P. Larrañaga A review of feature selection techniques in bioinformatics Bioinformatics 23 2007 2507 2517
    • (2007) Bioinformatics , vol.23 , pp. 2507-2517
    • Saeys, Y.1    Inza, I.2    Larrañaga, P.3
  • 13
    • 77956612020 scopus 로고    scopus 로고
    • Text-independent speaker verification using ant colony optimization-based selected features
    • S. Nemati, and M.E. Basiri Text-independent speaker verification using ant colony optimization-based selected features Expert Syst. Appl. 38 2011 620 630
    • (2011) Expert Syst. Appl. , vol.38 , pp. 620-630
    • Nemati, S.1    Basiri, M.E.2
  • 14
    • 76749153275 scopus 로고    scopus 로고
    • A modified ant colony optimization algorithm for tumor marker gene selection
    • H. Yu, G. Gu, H. Liu, J. Shen, and J. Zhao A modified ant colony optimization algorithm for tumor marker gene selection Genomics Proteomics Bioinform. 7 2009 200 208
    • (2009) Genomics Proteomics Bioinform. , vol.7 , pp. 200-208
    • Yu, H.1    Gu, G.2    Liu, H.3    Shen, J.4    Zhao, J.5
  • 15
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • I. Guyon, J. Weston, S. Barnhill, and V. Vapnik Gene selection for cancer classification using support vector machines Mach. Learn. 46 2002 389 422
    • (2002) Mach. Learn. , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 16
    • 56349169042 scopus 로고    scopus 로고
    • A hybrid SOFM-SVR with a filter-based feature selection for stock market forecasting
    • C.-L. Huang, and C.-Y. Tsai A hybrid SOFM-SVR with a filter-based feature selection for stock market forecasting Expert Syst. Appl. 36 2009 1529 1539
    • (2009) Expert Syst. Appl. , vol.36 , pp. 1529-1539
    • Huang, C.-L.1    Tsai, C.-Y.2
  • 17
    • 67349284734 scopus 로고    scopus 로고
    • Ant colony and particle swarm optimization for financial classification problems
    • Y. Marinakis, M. Marinaki, M. Doumpos, and C. Zopounidis Ant colony and particle swarm optimization for financial classification problems Expert Syst. Appl. 36 2009 10604 10611
    • (2009) Expert Syst. Appl. , vol.36 , pp. 10604-10611
    • Marinakis, Y.1    Marinaki, M.2    Doumpos, M.3    Zopounidis, C.4
  • 19
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
    • H. Peng, F. Long, and C. Ding Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy IEEE Trans. Pattern Anal. Mach. Intell. 27 2005 1226 1238
    • (2005) IEEE Trans. Pattern Anal. Mach. Intell. , vol.27 , pp. 1226-1238
    • Peng, H.1    Long, F.2    Ding, C.3
  • 20
    • 0017535866 scopus 로고
    • A branch and bound algorithm for feature subset selection
    • P.M. Narendra, and K. Fukunaga A branch and bound algorithm for feature subset selection IEEE Trans. Comput. 26 1977 917 922
    • (1977) IEEE Trans. Comput. , vol.26 , pp. 917-922
    • Narendra, P.M.1    Fukunaga, K.2
  • 22
    • 76749129275 scopus 로고    scopus 로고
    • Supervised feature selection by clustering using conditional mutual information-based distances
    • J. Martínez Sotoca, and F. Pla Supervised feature selection by clustering using conditional mutual information-based distances Pattern Recognit. 43 2010 2068 2081
    • (2010) Pattern Recognit. , vol.43 , pp. 2068-2081
    • Martínez Sotoca, J.1    Pla, F.2
  • 23
    • 69149109819 scopus 로고    scopus 로고
    • A novel ACO-GA hybrid algorithm for feature selection in protein function prediction
    • S. Nemati, M.E. Basiri, N. Ghasem-Aghaee, and M.H. Aghdam A novel ACO-GA hybrid algorithm for feature selection in protein function prediction Expert Syst. Appl. 36 2009 12086 12094
    • (2009) Expert Syst. Appl. , vol.36 , pp. 12086-12094
    • Nemati, S.1    Basiri, M.E.2    Ghasem-Aghaee, N.3    Aghdam, M.H.4
  • 24
  • 25
    • 84875245118 scopus 로고    scopus 로고
    • Efficient ant colony optimization for image feature selection
    • B. Chen, L. Chen, and Y. Chen Efficient ant colony optimization for image feature selection Signal Process. 93 2013 1566 1576
    • (2013) Signal Process. , vol.93 , pp. 1566-1576
    • Chen, B.1    Chen, L.2    Chen, Y.3
  • 26
    • 80051952405 scopus 로고    scopus 로고
    • Ant colony optimization: Overview and recent advances
    • Springer, US
    • M. Dorigo, T. Stützle, Ant colony optimization: overview and recent advances, in: Handbook of Metaheuristics, Springer, US, 2010, pp. 227-263.
    • (2010) Handbook of Metaheuristics , pp. 227-263
    • Dorigo, M.1    Stützle, T.2
  • 28
    • 0031122887 scopus 로고    scopus 로고
    • Ant colony system: A cooperative learning approach to the traveling salesman problem
    • M. Dorigo, and L.M. Gambardella Ant colony system: a cooperative learning approach to the traveling salesman problem IEEE Trans. Evol. Comput. 1 1997 53 66
    • (1997) IEEE Trans. Evol. Comput. , vol.1 , pp. 53-66
    • Dorigo, M.1    Gambardella, L.M.2
  • 29
    • 0030759617 scopus 로고    scopus 로고
    • Ant colonies for the travelling salesman problem
    • M. Dorigo, and L.M. Gambardella Ant colonies for the travelling salesman problem Biosystems 43 1997 73 81
    • (1997) Biosystems , vol.43 , pp. 73-81
    • Dorigo, M.1    Gambardella, L.M.2
  • 31
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • I. Guyon, and A. Elisseeff An introduction to variable and feature selection J. Mach. Learn. Res. 3 2003 1157 1182
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 32
    • 33646258047 scopus 로고    scopus 로고
    • Random subspace method for multivariate feature selection
    • C. Lai, M.J.T. Reinders, and L. Wessels Random subspace method for multivariate feature selection Pattern Recognit. Lett. 27 2006 1067 1076
    • (2006) Pattern Recognit. Lett. , vol.27 , pp. 1067-1076
    • Lai, C.1    Reinders, M.J.T.2    Wessels, L.3
  • 33
    • 3943113604 scopus 로고    scopus 로고
    • Theoretical comparison between the Gini Index and information gain criteria
    • L.E. Raileanu, and K. Stoffel Theoretical comparison between the Gini Index and information gain criteria Ann. Math. Artif. Intell. 41 2004 77 93
    • (2004) Ann. Math. Artif. Intell. , vol.41 , pp. 77-93
    • Raileanu, L.E.1    Stoffel, K.2
  • 37
    • 33744584654 scopus 로고
    • Induction of decision trees
    • J.R. Quinlan Induction of decision trees Mach. Learn. 1 1986 81 106
    • (1986) Mach. Learn. , vol.1 , pp. 81-106
    • Quinlan, J.R.1
  • 38
    • 80052324437 scopus 로고    scopus 로고
    • Feature selection for high-dimensional data: A Pearson redundancy based filter
    • Springer, Berlin, Heidelberg
    • J. Biesiada, W. Duch, Feature selection for high-dimensional data: a Pearson redundancy based filter, in: Computer Recognition Systems, vol. 2, Springer, Berlin, Heidelberg, 2007, pp. 242-249.
    • (2007) Computer Recognition Systems , vol.2 , pp. 242-249
    • Biesiada, J.1    Duch, W.2
  • 42
    • 84866031290 scopus 로고    scopus 로고
    • Selecting feature subset for high dimensional data via the propositional FOIL rules
    • G. Wang, Q. Song, B. Xu, and Y. Zhou Selecting feature subset for high dimensional data via the propositional FOIL rules Pattern Recognit. 46 2013 199 214
    • (2013) Pattern Recognit. , vol.46 , pp. 199-214
    • Wang, G.1    Song, Q.2    Xu, B.3    Zhou, Y.4
  • 45
    • 25144492516 scopus 로고    scopus 로고
    • Efficient feature selection via analysis of relevance and redundancy
    • L. Yu, and H. Liu Efficient feature selection via analysis of relevance and redundancy J. Mach. Learn. Res. 5 2004 1205 1224
    • (2004) J. Mach. Learn. Res. , vol.5 , pp. 1205-1224
    • Yu, L.1    Liu, H.2
  • 46
    • 77951139898 scopus 로고    scopus 로고
    • A discrete particle swarm optimization method for feature selection in binary classification problems
    • A. Unler, and A. Murat A discrete particle swarm optimization method for feature selection in binary classification problems Eur. J. Oper. Res. 206 2010 528 539
    • (2010) Eur. J. Oper. Res. , vol.206 , pp. 528-539
    • Unler, A.1    Murat, A.2
  • 47
    • 33846695029 scopus 로고    scopus 로고
    • Framework for efficient feature selection in genetic algorithm based data mining
    • R. Sikora, and S. Piramuthu Framework for efficient feature selection in genetic algorithm based data mining Eur. J. Oper. Res. 180 2007 723 737
    • (2007) Eur. J. Oper. Res. , vol.180 , pp. 723-737
    • Sikora, R.1    Piramuthu, S.2
  • 48
    • 0032028297 scopus 로고    scopus 로고
    • Feature subset selection using a genetic algorithm
    • J. Yang, and V. Honavar Feature subset selection using a genetic algorithm IEEE Intell. Syst. Their Appl. 13 1998 44 49
    • (1998) IEEE Intell. Syst. Their Appl. , vol.13 , pp. 44-49
    • Yang, J.1    Honavar, V.2
  • 51
    • 31144448615 scopus 로고    scopus 로고
    • Using simulated annealing to optimize the feature selection problem in marketing applications
    • R. Meiri, and J. Zahavi Using simulated annealing to optimize the feature selection problem in marketing applications Eur. J. Oper. Res. 171 2006 842 858
    • (2006) Eur. J. Oper. Res. , vol.171 , pp. 842-858
    • Meiri, R.1    Zahavi, J.2
  • 53
    • 33750591809 scopus 로고    scopus 로고
    • Feature selection using Decision Tree and classification through Proximal Support Vector Machine for fault diagnostics of roller bearing
    • V. Sugumaran, V. Muralidharan, and K.I. Ramachandran Feature selection using Decision Tree and classification through Proximal Support Vector Machine for fault diagnostics of roller bearing Mech. Syst. Signal Process. 21 2007 930 942
    • (2007) Mech. Syst. Signal Process. , vol.21 , pp. 930-942
    • Sugumaran, V.1    Muralidharan, V.2    Ramachandran, K.I.3
  • 55
    • 67349242422 scopus 로고    scopus 로고
    • A filter model for feature subset selection based on genetic algorithm
    • M.E. ElAlami A filter model for feature subset selection based on genetic algorithm Knowl.-Based Syst. 22 2009 356 362
    • (2009) Knowl.-Based Syst. , vol.22 , pp. 356-362
    • Elalami, M.E.1


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