메뉴 건너뛰기




Volumn 147, Issue 1, 2015, Pages 271-279

An advanced ACO algorithm for feature subset selection

Author keywords

Ant colony optimization (ACO); Binary ACO; Classification; Feature selection; Wrapper

Indexed keywords

ANT COLONY OPTIMIZATION; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DATA MINING; FEATURE EXTRACTION; GENETIC ALGORITHMS; GRAPH THEORY; HEURISTIC ALGORITHMS; OPTIMIZATION; PARTICLE SWARM OPTIMIZATION (PSO); PATTERN RECOGNITION SYSTEMS; SEARCH ENGINES;

EID: 84924050625     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.06.067     Document Type: Article
Times cited : (298)

References (45)
  • 1
    • 71549117600 scopus 로고    scopus 로고
    • Two cooperative ant colonies for feature selection using fuzzy models
    • Vieira S.M., Sousa J.M.C., Runkler T.A. Two cooperative ant colonies for feature selection using fuzzy models. Expert Syst. Appl. 2010, 37:2714-2723.
    • (2010) Expert Syst. Appl. , vol.37 , pp. 2714-2723
    • Vieira, S.M.1    Sousa, J.M.C.2    Runkler, T.A.3
  • 2
    • 77951295936 scopus 로고    scopus 로고
    • Feature selection for classification of hyperspectral data by SVM
    • Pal M., Foody G.M. Feature selection for classification of hyperspectral data by SVM. IEEE Trans. Geosci. Remote Sens. 2010, 48(5):2297-2307.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , Issue.5 , pp. 2297-2307
    • Pal, M.1    Foody, G.M.2
  • 3
    • 17044405923 scopus 로고    scopus 로고
    • Toward integrating feature selection algorithms for classification and clustering
    • Liu H., Yu L. Toward integrating feature selection algorithms for classification and clustering. IEEE Trans. Knowl. Data Eng. 2005, 17(4):491-502.
    • (2005) IEEE Trans. Knowl. Data Eng. , vol.17 , Issue.4 , pp. 491-502
    • Liu, H.1    Yu, L.2
  • 4
    • 77951494965 scopus 로고    scopus 로고
    • Feature selection based F-score and ACO algorithm in support vector machine
    • in: Proceedings of the 2nd International Symposium on Knowledge Acquisition and Modeling
    • S. Ding, Feature selection based F-score and ACO algorithm in support vector machine, in: Proceedings of the 2nd International Symposium on Knowledge Acquisition and Modeling, 2009.
    • (2009)
    • Ding, S.1
  • 5
    • 84862536593 scopus 로고    scopus 로고
    • A novel feature selection method based on normalized mutual information
    • Vinh L.T., Lee S., Park Y.-T., d'Auriol B.J. A novel feature selection method based on normalized mutual information. Appl. Intell. 2010, 37:100-120.
    • (2010) Appl. Intell. , vol.37 , pp. 100-120
    • Vinh, L.T.1    Lee, S.2    Park, Y.-T.3    d'Auriol, B.J.4
  • 7
    • 80052941913 scopus 로고    scopus 로고
    • A new local search based hybrid genetic algorithm for feature selection
    • Kabir M., Md.Shahjahan, Murase K. A new local search based hybrid genetic algorithm for feature selection. Neurocomputing 2011, 74:2914-2928.
    • (2011) Neurocomputing , vol.74 , pp. 2914-2928
    • Kabir, M.1    Shahjahan, M.D.2    Murase, K.3
  • 8
    • 84856271767 scopus 로고    scopus 로고
    • Replica inference approach to unsupervised multiscale image segmentation
    • Hu D., Ronhvde P., Nussinov Z. Replica inference approach to unsupervised multiscale image segmentation. Phys. Rev. E 2012, 85:016101.
    • (2012) Phys. Rev. E , vol.85 , pp. 016101
    • Hu, D.1    Ronhvde, P.2    Nussinov, Z.3
  • 9
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature selection
    • Kohavi R., John G. Wrappers for feature selection. Artif. Intell. 1997, 97(1-2):273-324.
    • (1997) Artif. Intell. , vol.97 , Issue.1-2 , pp. 273-324
    • Kohavi, R.1    John, G.2
  • 10
    • 47249156145 scopus 로고    scopus 로고
    • Using ant colony optimization-based selected features for predicting post-synaptic activity in proteins
    • EvoBIO, in: Lecture Notes in Computer Science, Italy.
    • M.E. Basiri, N. Ghasem-Aghaee, M.H. Aghdam, Using ant colony optimization-based selected features for predicting post-synaptic activity in proteins, EvoBIO, in: Lecture Notes in Computer Science, vol. 4973, 2008, 12-23, Italy.
    • (2008) , vol.4973 , pp. 12-23
    • Basiri, M.E.1    Ghasem-Aghaee, N.2    Aghdam, M.H.3
  • 11
    • 78751648113 scopus 로고    scopus 로고
    • A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets
    • Bermejo P., Gámez J.A., Puerta J.M. A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets. Pattern Recognit. Lett. 2001, 32:701-711.
    • (2001) Pattern Recognit. Lett. , vol.32 , pp. 701-711
    • Bermejo, P.1    Gámez, J.A.2    Puerta, J.M.3
  • 12
    • 34447343762 scopus 로고    scopus 로고
    • A hybrid genetic algorithm for feature selection wrapper based on mutual information
    • Huang J., Cai Y., Xu X. A hybrid genetic algorithm for feature selection wrapper based on mutual information. Pattern Recognit. Lett. 2007, 28:1825-1844.
    • (2007) Pattern Recognit. Lett. , vol.28 , pp. 1825-1844
    • Huang, J.1    Cai, Y.2    Xu, X.3
  • 13
    • 33845621875 scopus 로고    scopus 로고
    • A hybrid approach for feature subset selection using neural networks and ant colony optimization
    • Sivagaminathan R.K., Ramakrishnan S. A hybrid approach for feature subset selection using neural networks and ant colony optimization. Expert Syst. Appl. 2007, 33:49-60.
    • (2007) Expert Syst. Appl. , vol.33 , pp. 49-60
    • Sivagaminathan, R.K.1    Ramakrishnan, S.2
  • 14
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Guyon I., Elisseeff A. An introduction to variable and feature selection. J. Mach. Learn. Res. 2003, 3:1157-1182.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 15
    • 0013326060 scopus 로고    scopus 로고
    • Feature selection for classification
    • Dash M., Liu H. Feature selection for classification. Intell. Data Anal. 1997, 1:131-156.
    • (1997) Intell. Data Anal. , vol.1 , pp. 131-156
    • Dash, M.1    Liu, H.2
  • 16
    • 77957925386 scopus 로고    scopus 로고
    • Chaotic maps based on binary particle swarm optimization for feature selection
    • Chuang L.Y., Yang C.H., Li J.C. Chaotic maps based on binary particle swarm optimization for feature selection. Appl. Soft Comput. 2011, 11:239-248.
    • (2011) Appl. Soft Comput. , vol.11 , pp. 239-248
    • Chuang, L.Y.1    Yang, C.H.2    Li, J.C.3
  • 17
    • 79957970608 scopus 로고    scopus 로고
    • Improved binary particle swarm optimization using catfish effect for feature selection
    • Chuang L.Y., Tsai S.W., Yang C.H. Improved binary particle swarm optimization using catfish effect for feature selection. Expert Syst. Appl. 2011, 38:12699-12707.
    • (2011) Expert Syst. Appl. , vol.38 , pp. 12699-12707
    • Chuang, L.Y.1    Tsai, S.W.2    Yang, C.H.3
  • 18
    • 33845523839 scopus 로고    scopus 로고
    • Feature selection based on rough sets and particle swarm optimization.
    • Wang X., Yang J., Teng X., Xia W., Jensen R. Feature selection based on rough sets and particle swarm optimization. Pattern Recognit. Lett. 2007, 28(4):459-471.
    • (2007) Pattern Recognit. Lett. , vol.28 , Issue.4 , pp. 459-471
    • Wang, X.1    Yang, J.2    Teng, X.3    Xia, W.4    Jensen, R.5
  • 20
    • 84866152441 scopus 로고    scopus 로고
    • Facing the classification of binary problems with a GSA-SVM hybrid system
    • Sarafrazi S., Nezamabadi-pour H. Facing the classification of binary problems with a GSA-SVM hybrid system. Math. Comput. Model. 2013, 57(1-2):270-278.
    • (2013) Math. Comput. Model. , vol.57 , Issue.1-2 , pp. 270-278
    • Sarafrazi, S.1    Nezamabadi-pour, H.2
  • 21
    • 84888624140 scopus 로고    scopus 로고
    • Feature subset selection using improved binary gravitational search algorithm
    • Rashedi E., Nezamabadi-pour H. Feature subset selection using improved binary gravitational search algorithm. J. Intell. Fuzzy Syst. 2014, 26(3):1211-1221.
    • (2014) J. Intell. Fuzzy Syst. , vol.26 , Issue.3 , pp. 1211-1221
    • Rashedi, E.1    Nezamabadi-pour, H.2
  • 22
    • 84871925258 scopus 로고    scopus 로고
    • A simultaneous feature adaptation and feature selection method for content-based image retrieval systems
    • Rashedi E., Nezamabadi-pour H., Saryazdi S. A simultaneous feature adaptation and feature selection method for content-based image retrieval systems. Knowl. Based Syst. 2013, 39:85-94.
    • (2013) Knowl. Based Syst. , vol.39 , pp. 85-94
    • Rashedi, E.1    Nezamabadi-pour, H.2    Saryazdi, S.3
  • 23
    • 84901418243 scopus 로고    scopus 로고
    • Ant colony optimization: a new meta-heuristic
    • in: Proceedings of the IEEE Congress on Evolutionary Computing
    • M. Dorigo, G.D. Caro, Ant colony optimization: a new meta-heuristic, in: Proceedings of the IEEE Congress on Evolutionary Computing, 1999.
    • (1999)
    • Dorigo, M.1    Caro, G.D.2
  • 24
    • 0030082551 scopus 로고    scopus 로고
    • The ant system: optimization by a colony of cooperative agents
    • Dorigo M., Maniezzo V., Colorni A. The ant system: optimization by a colony of cooperative agents. IEEE Trans. Syst. Man Cybern. 1996, 26(1):1-13.
    • (1996) IEEE Trans. Syst. Man Cybern. , vol.26 , Issue.1 , pp. 1-13
    • Dorigo, M.1    Maniezzo, V.2    Colorni, A.3
  • 25
    • 33845667087 scopus 로고    scopus 로고
    • Feature subset selection using ant colony optimization
    • Al-Ani A. Feature subset selection using ant colony optimization. Int. J. Comput. Intell. 2005, 2(1):53-58.
    • (2005) Int. J. Comput. Intell. , vol.2 , Issue.1 , pp. 53-58
    • Al-Ani, A.1
  • 26
    • 0030759617 scopus 로고    scopus 로고
    • Ant colonies for the traveling salesman problem
    • Dorigo M., Gambardella L.M. Ant colonies for the traveling salesman problem. BioSystems 1997, 43:73-81.
    • (1997) BioSystems , vol.43 , pp. 73-81
    • Dorigo, M.1    Gambardella, L.M.2
  • 27
    • 0031122887 scopus 로고    scopus 로고
    • Ant colony system: a cooperative learning approach to the traveling salesman problem
    • Dorigo M., Gambardella L.M. Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. Evolut. Comput. 1997, 1(1):53-66.
    • (1997) IEEE Trans. Evolut. Comput. , vol.1 , Issue.1 , pp. 53-66
    • Dorigo, M.1    Gambardella, L.M.2
  • 28
    • 28944454561 scopus 로고    scopus 로고
    • Ant colony optimization: introduction and recent trends
    • Blum C. Ant colony optimization: introduction and recent trends. Phys. Life Rev. 2005, 2:353-373.
    • (2005) Phys. Life Rev. , vol.2 , pp. 353-373
    • Blum, C.1
  • 29
    • 28444485325 scopus 로고    scopus 로고
    • Feature selection using the hybrid of ant colony optimization and mutual information for the forecaster
    • in: Proceeding of the 4th International Conference on Machine Learning and Cybernetics
    • C.K. Zhang, H. Hu, Feature selection using the hybrid of ant colony optimization and mutual information for the forecaster, in: Proceeding of the 4th International Conference on Machine Learning and Cybernetics, 2005, pp. 1728-1732.
    • (2005) , pp. 1728-1732
    • Zhang, C.K.1    Hu, H.2
  • 30
    • 55749111514 scopus 로고    scopus 로고
    • Application of ant colony optimization for feature selection in text categorization
    • in: Proceeding of 5th IEEE Congress on Evolutionary Computation, Hong Kong
    • M.H. Aghdam, N. Ghasem-Aghaee. M.E. Basiri, Application of ant colony optimization for feature selection in text categorization, in: Proceeding of 5th IEEE Congress on Evolutionary Computation, Hong Kong, 2008.
    • (2008)
    • Aghdam, M.H.1    Ghasem-Aghaee, N.2    Basiri, M.E.3
  • 31
    • 69149109819 scopus 로고    scopus 로고
    • A novel ACO-GA hybrid algorithm for feature selection in protein function prediction
    • Nemati S., Basiri M.E., Ghasem-Aghayee N., Aghdam M.H. A novel ACO-GA hybrid algorithm for feature selection in protein function prediction. Expert Syst. Appl. 2009, 36:12086-12094.
    • (2009) Expert Syst. Appl. , vol.36 , pp. 12086-12094
    • Nemati, S.1    Basiri, M.E.2    Ghasem-Aghayee, N.3    Aghdam, M.H.4
  • 32
    • 78149316217 scopus 로고    scopus 로고
    • Hybrid feature selection algorithm based on dynamic weighted ant colony algorithm
    • in: Proceedings of the 9th International Conference on Machine Learning and Cybernetics, Qingdao
    • S.H. Xiong, J.Y. Wang, H. Lin, Hybrid feature selection algorithm based on dynamic weighted ant colony algorithm, in: Proceedings of the 9th International Conference on Machine Learning and Cybernetics, Qingdao, 2010.
    • (2010)
    • Xiong, S.H.1    Wang, J.Y.2    Lin, H.3
  • 33
    • 72449177821 scopus 로고    scopus 로고
    • A rough set approach to feature selection based on ant colony optimization
    • Chen Y., Miao D., Wang R. A rough set approach to feature selection based on ant colony optimization. Pattern Recognit. Lett. 2010, 31:226-233.
    • (2010) Pattern Recognit. Lett. , vol.31 , pp. 226-233
    • Chen, Y.1    Miao, D.2    Wang, R.3
  • 34
    • 84924071071 scopus 로고    scopus 로고
    • Feature selection using binary ant algorithm
    • in: Proceedings of the Frist Joint Congress on Fuzzy and Intelligent Systems, Mashhad, Iran, August 2007 (in Farsi).
    • H. Touhidi, H. Nezamabadi-pour, S. Saryazdi, Feature selection using binary ant algorithm, in: Proceedings of the Frist Joint Congress on Fuzzy and Intelligent Systems, Mashhad, Iran, August 2007 (in Farsi).
    • Touhidi, H.1    Nezamabadi-pour, H.2    Saryazdi, S.3
  • 35
    • 84888580579 scopus 로고    scopus 로고
    • A new feature selection algorithm based on binary ant colony optimization
    • in: Proceedings of the 5th Conference on Information and Knowledge Technology, IKT, Shiraz, Iran
    • S. Kashef, H. Nezamabadi-pour, A new feature selection algorithm based on binary ant colony optimization, in: Proceedings of the 5th Conference on Information and Knowledge Technology, IKT, Shiraz, Iran, 2013.
    • (2013)
    • Kashef, S.1    Nezamabadi-pour, H.2
  • 36
    • 84855907953 scopus 로고    scopus 로고
    • An enhanced ACO algorithm to select features for text categorization and its parallelization
    • Janaki Meena M., Chandran K.R., Karthik A., Vijay Samuel A. An enhanced ACO algorithm to select features for text categorization and its parallelization. Expert Syst. Appl. 2012, 39:5861-5871.
    • (2012) Expert Syst. Appl. , vol.39 , pp. 5861-5871
    • Janaki Meena, M.1    Chandran, K.R.2    Karthik, A.3    Vijay Samuel, A.4
  • 38
    • 2942530954 scopus 로고    scopus 로고
    • Designing digital IIR filters using ant colony optimization algorithm
    • Karaboga N., Kalinli A., Karaboga D. Designing digital IIR filters using ant colony optimization algorithm. Eng. Appl. Artif. Intell. 2004, 17:301-309.
    • (2004) Eng. Appl. Artif. Intell. , vol.17 , pp. 301-309
    • Karaboga, N.1    Kalinli, A.2    Karaboga, D.3
  • 39
    • 69249222735 scopus 로고    scopus 로고
    • TACO-miner: an ant colony based algorithm for rule extraction from trained neural networks
    • Ozbakir L., Baykasoglu A., Kulluk S., Yapici H. TACO-miner: an ant colony based algorithm for rule extraction from trained neural networks. Expert Syst. Appl. 2009, 36:12295-12305.
    • (2009) Expert Syst. Appl. , vol.36 , pp. 12295-12305
    • Ozbakir, L.1    Baykasoglu, A.2    Kulluk, S.3    Yapici, H.4
  • 40
    • 84875245118 scopus 로고    scopus 로고
    • Efficient ant colony optimization for image feature selection
    • Chen B., Chen L., Chen Y. Efficient ant colony optimization for image feature selection. Signal Process. 2013, 93:1566-1576.
    • (2013) Signal Process. , vol.93 , pp. 1566-1576
    • Chen, B.1    Chen, L.2    Chen, Y.3
  • 41
    • 25844469853 scopus 로고    scopus 로고
    • Combining Rough and Fuzzy Sets for Feature Selection (Ph.D. thesis)
    • University of Edinburgh
    • R. Jensen, Combining Rough and Fuzzy Sets for Feature Selection (Ph.D. thesis), University of Edinburgh, 2005.
    • (2005)
    • Jensen, R.1
  • 42
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy
    • Peng H., Long F., Ding C. Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans. Pattern Anal. Mach. Intell. 2005, 27(8).
    • (2005) IEEE Trans. Pattern Anal. Mach. Intell. , vol.27 , Issue.8
    • Peng, H.1    Long, F.2    Ding, C.3
  • 43
    • 70350705845 scopus 로고    scopus 로고
    • ACO-based hybrid classification system with feature subset selection and model parameters optimization
    • Huang C.L. ACO-based hybrid classification system with feature subset selection and model parameters optimization. Neurocomputing 2009, 73:438-448.
    • (2009) Neurocomputing , vol.73 , pp. 438-448
    • Huang, C.L.1
  • 44
    • 78650540340 scopus 로고    scopus 로고
    • Applying electromagnetism-like mechanism for feature selection
    • Su C.T., Lin H.C. Applying electromagnetism-like mechanism for feature selection. Inf. Sci. 2011, 181:972-986.
    • (2011) Inf. Sci. , vol.181 , pp. 972-986
    • Su, C.T.1    Lin, H.C.2
  • 45
    • 84924052493 scopus 로고    scopus 로고
    • Center for Machine Learning and Intelligent Systems
    • UCI Machine Learning Repository. Center for Machine Learning and Intelligent Systems. http://www.archieve.ics.uci.edu/ml/datasets.html.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.