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Volumn 271, Issue , 2014, Pages 65-81

Erratum: Quick attribute reduct algorithm for neighborhood rough set model (Information Sciences (2014) 271 (65-81) DOI: 10.1016/j.ins.2014.02.093);Quick attribute reduct algorithm for neighborhood rough set model

Author keywords

Attribute reduct; Bucket; Neighborhood rough set; Rough set

Indexed keywords

BIG DATA;

EID: 84898797239     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2015.03.057     Document Type: Erratum
Times cited : (143)

References (45)
  • 1
    • 33749680310 scopus 로고    scopus 로고
    • Rudiments of rough sets
    • Z. Pawlak, and A. Skowron Rudiments of rough sets Inform. Sci. 177 1 2007 3 27
    • (2007) Inform. Sci. , vol.177 , Issue.1 , pp. 3-27
    • Pawlak, Z.1    Skowron, A.2
  • 3
    • 10944249572 scopus 로고    scopus 로고
    • Semantics-preserving dimensionality reduction: Rough and fuzzy-rough-based approaches
    • R. Jensen, and Q. Shen Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches IEEE Trans. Knowl. Data Eng. 16 12 2004 1457 1471
    • (2004) IEEE Trans. Knowl. Data Eng. , vol.16 , Issue.12 , pp. 1457-1471
    • Jensen, R.1    Shen, Q.2
  • 4
    • 32644440353 scopus 로고    scopus 로고
    • Information-preserving hybrid data reduction based on fuzzy-rough techniques
    • Q. Hu, D. Yu, and Z. Xie Information-preserving hybrid data reduction based on fuzzy-rough techniques Pattern Recogn. Lett. 27 5 2006 414 423
    • (2006) Pattern Recogn. Lett. , vol.27 , Issue.5 , pp. 414-423
    • Hu, Q.1    Yu, D.2    Xie, Z.3
  • 5
    • 42949087870 scopus 로고    scopus 로고
    • Mixed feature selection based on granulation and approximation
    • Q. Hu, J. Liu, and D. Yu Mixed feature selection based on granulation and approximation Knowl.-Based Syst. 21 4 2008 294 304
    • (2008) Knowl.-Based Syst. , vol.21 , Issue.4 , pp. 294-304
    • Hu, Q.1    Liu, J.2    Yu, D.3
  • 6
    • 0242302657 scopus 로고    scopus 로고
    • Consistency-based search in feature selection
    • M. Dash, and H. Liu Consistency-based search in feature selection Artif. Intell. 151 1-2 2003 155 176
    • (2003) Artif. Intell. , vol.151 , Issue.12 , pp. 155-176
    • Dash, M.1    Liu, H.2
  • 7
    • 85065703189 scopus 로고    scopus 로고
    • Correlation-based feature selection for discrete and numeric class machine learning
    • Stanford University, Stanford, CA, USA, June 29-July 2, 2000
    • M.A. Hall, Correlation-based feature selection for discrete and numeric class machine learning, in: Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29-July 2, 2000, pp. 359-366.
    • Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000) , pp. 359-366
    • Hall, M.A.1
  • 8
    • 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
  • 9
    • 33847646332 scopus 로고    scopus 로고
    • Wrapper-Filter feature selection algorithm using a memetic framework
    • Z. Zhu, Y.-S. Ong, and M. Dash Wrapper-Filter feature selection algorithm using a memetic framework IEEE Trans. Syst., Man, Cybern., Part B 37 1 2007 70 76
    • (2007) IEEE Trans. Syst., Man, Cybern., Part B , vol.37 , Issue.1 , pp. 70-76
    • Zhu, Z.1    Ong, Y.-S.2    Dash, M.3
  • 10
    • 0035416447 scopus 로고    scopus 로고
    • Using rough sets with heuristics for feature selection
    • N. Zhong, J. Dong, and S. Ohsuga Using rough sets with heuristics for feature selection J. Intell. Inform. Syst. 16 3 2001 199 214
    • (2001) J. Intell. Inform. Syst. , vol.16 , Issue.3 , pp. 199-214
    • Zhong, N.1    Dong, J.2    Ohsuga, S.3
  • 11
    • 0037332841 scopus 로고    scopus 로고
    • Rough set methods in feature selection and recognition
    • R.W. Swiniarski, and A. Skowron Rough set methods in feature selection and recognition Pattern Recogn. Lett. 24 6 2003 833 849
    • (2003) Pattern Recogn. Lett. , vol.24 , Issue.6 , pp. 833-849
    • Swiniarski, R.W.1    Skowron, A.2
  • 12
    • 84856802348 scopus 로고    scopus 로고
    • A new framework for incremental rule induction based on rough sets
    • 2011
    • S. Tsumoto, A new framework for incremental rule induction based on rough sets, in: GrC, 2011, pp. 681-686.
    • GrC , pp. 681-686
    • Tsumoto, S.1
  • 13
    • 79958865000 scopus 로고    scopus 로고
    • Combined rough sets with flow graph and formal concept analysis for business aviation decision-making
    • Y.-P.O. Yang, H.-M. Shieh, G.-H. Tzeng, L. Yen, and C.-C. Chan Combined rough sets with flow graph and formal concept analysis for business aviation decision-making J. Intell. Inform. Syst. 36 3 2011 347 366
    • (2011) J. Intell. Inform. Syst. , vol.36 , Issue.3 , pp. 347-366
    • Yang, Y.-P.O.1    Shieh, H.-M.2    Tzeng, G.-H.3    Yen, L.4    Chan, C.-C.5
  • 14
    • 52649111659 scopus 로고    scopus 로고
    • Rough rule extracting from various conditions: Incremental and approximate approaches for inconsistent data
    • Y. Liu, C. Xu, Q. Zhang, and Y. Pan Rough rule extracting from various conditions: incremental and approximate approaches for inconsistent data Fundam. Inform. 84 3-4 2008 403 427
    • (2008) Fundam. Inform. , vol.84 , Issue.34 , pp. 403-427
    • Liu, Y.1    Xu, C.2    Zhang, Q.3    Pan, Y.4
  • 15
    • 77958606383 scopus 로고    scopus 로고
    • Infobright Analytic database engine using rough sets and granular computing
    • D. Slezak, P. Synak, J. Wroblewski, G. Toppin, Infobright Analytic database engine using rough sets and granular computing, in: GrC, 2010, pp. 432-437.
    • (2010) GrC , pp. 432-437
    • Slezak, D.1    Synak, P.2    Wroblewski, J.3    Toppin, G.4
  • 16
    • 46749140199 scopus 로고    scopus 로고
    • Neighborhood rough set based heterogeneous feature subset selection
    • Q. Hu, D. Yu, J. Liu, and C. Wu Neighborhood rough set based heterogeneous feature subset selection Inform. Sci. 178 18 2008 3577 3594
    • (2008) Inform. Sci. , vol.178 , Issue.18 , pp. 3577-3594
    • Hu, Q.1    Yu, D.2    Liu, J.3    Wu, C.4
  • 17
    • 0032147655 scopus 로고    scopus 로고
    • A comparative study of fuzzy sets and rough sets
    • Y.Y. Yao A comparative study of fuzzy sets and rough sets Inform. Sci. 109 1998 21 47
    • (1998) Inform. Sci. , vol.109 , pp. 21-47
    • Yao, Y.Y.1
  • 18
    • 33645801018 scopus 로고    scopus 로고
    • Fuzzy probabilistic approximation spaces and their information measures
    • Q. Hu, D. Yu, Z. Xie, and J. Liu Fuzzy probabilistic approximation spaces and their information measures IEEE Trans. Fuzzy Syst. 14 2 2006 191 201
    • (2006) IEEE Trans. Fuzzy Syst. , vol.14 , Issue.2 , pp. 191-201
    • Hu, Q.1    Yu, D.2    Xie, Z.3    Liu, J.4
  • 20
    • 84858440271 scopus 로고    scopus 로고
    • Tolerance spaces: Origins, theoretical aspects and applications
    • J.F. Peters, and P. Wasilewski Tolerance spaces: origins, theoretical aspects and applications Inform. Sci. 195 2012 211 225
    • (2012) Inform. Sci. , vol.195 , pp. 211-225
    • Peters, J.F.1    Wasilewski, P.2
  • 21
    • 0033719032 scopus 로고    scopus 로고
    • A generalized definition of rough approximations based on similarity
    • R. Slowinski, and D. Vanderpooten A generalized definition of rough approximations based on similarity IEEE Trans. Knowl. Data Eng. 12 2 2000 331 336
    • (2000) IEEE Trans. Knowl. Data Eng. , vol.12 , Issue.2 , pp. 331-336
    • Slowinski, R.1    Vanderpooten, D.2
  • 23
    • 84860268481 scopus 로고    scopus 로고
    • Covering based rough set approximations
    • Y. Yao, and B. Yao Covering based rough set approximations Inform. Sci. 200 2012 91 107
    • (2012) Inform. Sci. , vol.200 , pp. 91-107
    • Yao, Y.1    Yao, B.2
  • 24
    • 84860278722 scopus 로고    scopus 로고
    • The fourth type of covering-based rough sets
    • W. Zhu, and F.-Y. Wang The fourth type of covering-based rough sets Inform. Sci. 201 2012 80 92
    • (2012) Inform. Sci. , vol.201 , pp. 80-92
    • Zhu, W.1    Wang, F.-Y.2
  • 25
    • 67349152755 scopus 로고    scopus 로고
    • Relationship among basic concepts in covering-based rough sets
    • W. Zhu Relationship among basic concepts in covering-based rough sets Inform. Sci. 179 14 2009 2478 2486
    • (2009) Inform. Sci. , vol.179 , Issue.14 , pp. 2478-2486
    • Zhu, W.1
  • 26
    • 34347243171 scopus 로고    scopus 로고
    • On three types of covering-based rough sets
    • W. Zhu, and F.-Y. Wang On three types of covering-based rough sets IEEE Trans. Knowl. Data Eng. 19 8 2007 1131 1144
    • (2007) IEEE Trans. Knowl. Data Eng. , vol.19 , Issue.8 , pp. 1131-1144
    • Zhu, W.1    Wang, F.-Y.2
  • 28
    • 70450043674 scopus 로고    scopus 로고
    • First GrC model - Neighborhood systems the most general rough set models
    • X. Yang, X. Li, T.Y. Lin, First GrC model - neighborhood systems the most general rough set models, in: GrC, 2009, pp. 691-695.
    • (2009) GrC , pp. 691-695
    • Yang, X.1    Li, X.2    Lin, T.Y.3
  • 29
    • 77955091406 scopus 로고    scopus 로고
    • Selecting discrete and continuous features based on neighborhood decision error minimization
    • Q. Hu, W. Pedrycz, D. Yu, and J. Lang Selecting discrete and continuous features based on neighborhood decision error minimization IEEE Trans. Syst., Man, Cybern., Part B 40 1 2010 137 150
    • (2010) IEEE Trans. Syst., Man, Cybern., Part B , vol.40 , Issue.1 , pp. 137-150
    • Hu, Q.1    Pedrycz, W.2    Yu, D.3    Lang, J.4
  • 30
    • 36148978191 scopus 로고    scopus 로고
    • Neighborhood classifiers
    • Q. Hu, D. Yu, and Z. Xie Neighborhood classifiers Expert Syst. Appl. 34 2 2008 866 876
    • (2008) Expert Syst. Appl. , vol.34 , Issue.2 , pp. 866-876
    • Hu, Q.1    Yu, D.2    Xie, Z.3
  • 31
    • 80054063216 scopus 로고    scopus 로고
    • Rule learning for classification based on neighborhood covering reduction
    • Y. Du, Q. Hu, P. Zhu, and P. Ma Rule learning for classification based on neighborhood covering reduction Inform. Sci. 181 24 2011 5457 5467
    • (2011) Inform. Sci. , vol.181 , Issue.24 , pp. 5457-5467
    • Du, Y.1    Hu, Q.2    Zhu, P.3    Ma, P.4
  • 32
    • 0004174560 scopus 로고
    • Theoretical Aspects of Reasoning about Data Springer, Formerly Kluwer Academic Publishers Boston, Dordrecht, London
    • Z. Pawlak Rough Sets Theoretical Aspects of Reasoning about Data 1991 Springer, Formerly Kluwer Academic Publishers Boston, Dordrecht, London
    • (1991) Rough Sets
    • Pawlak, Z.1
  • 33
    • 0002395767 scopus 로고
    • The discernibility matrices and functions in information systems
    • A. Skowron, and C. Rauszer The discernibility matrices and functions in information systems Intell. Decis. Support 1992 331 362
    • (1992) Intell. Decis. Support , pp. 331-362
    • Skowron, A.1    Rauszer, C.2
  • 34
    • 0141834859 scopus 로고    scopus 로고
    • Approaches to knowledge reductions in inconsistent systems
    • W.-X. Zhang, J.-S. Mi, and W.-Z. Wu Approaches to knowledge reductions in inconsistent systems Int. J. Intell. Syst. 18 9 2003 989 1000
    • (2003) Int. J. Intell. Syst. , vol.18 , Issue.9 , pp. 989-1000
    • Zhang, W.-X.1    Mi, J.-S.2    Wu, W.-Z.3
  • 35
    • 78651367557 scopus 로고    scopus 로고
    • Hybrid approaches to attribute reduction based on indiscernibility and discernibility relation
    • ISSN 0888-613X, doi:10.1016/j.ijar.2010.07.011. < >
    • J. Qian, D.Q. Miao, Z.H. Zhang, and W. Li Hybrid approaches to attribute reduction based on indiscernibility and discernibility relation Int. J. Approx. Reason. 52 2 2011 212 230 ISSN 0888-613X, doi:10.1016/j.ijar.2010.07.011. < http://dx.doi.org/10.1016/j.ijar.2010.07.011 >
    • (2011) Int. J. Approx. Reason. , vol.52 , Issue.2 , pp. 212-230
    • Qian, J.1    Miao, D.Q.2    Zhang, Z.H.3    Li, W.4
  • 36
    • 69749112944 scopus 로고    scopus 로고
    • Quick attribute reduction algorithm with hash
    • Y. Liu, R. Xiong, and J. Chu Quick attribute reduction algorithm with hash Chinese J. Comput. 32 8 2009 1493 1499
    • (2009) Chinese J. Comput. , vol.32 , Issue.8 , pp. 1493-1499
    • Liu, Y.1    Xiong, R.2    Chu, J.3
  • 37
    • 78651580998 scopus 로고    scopus 로고
    • Feature reduction with inconsistency
    • 10.4018/jcini.2010040106 ISSN 1557-395. < >
    • Y. Liu, Y. Jiang, and J. Yang Feature reduction with inconsistency Int. J. Cogn. Inform. Nat. Intell. 4 2 2010 77 87 10.4018/jcini.2010040106 ISSN 1557-395. < http://dx.doi.org/10.4018/jcini.2010040106 >
    • (2010) Int. J. Cogn. Inform. Nat. Intell. , vol.4 , Issue.2 , pp. 77-87
    • Liu, Y.1    Jiang, Y.2    Yang, J.3
  • 38
    • 0242322799 scopus 로고    scopus 로고
    • Rough set-aided keyword reduction for text categorization
    • A. Chouchoulas, and Q. Shen Rough set-aided keyword reduction for text categorization Appl. Artif. Intell. 15 9 2001 843 873
    • (2001) Appl. Artif. Intell. , vol.15 , Issue.9 , pp. 843-873
    • Chouchoulas, A.1    Shen, Q.2
  • 40
    • 0036662454 scopus 로고    scopus 로고
    • Decision table reduction based on conditional information entropy
    • G. Wang, H. Yu, and D. Yang Decision table reduction based on conditional information entropy Chinese J. Comput. 25 7 2002 759 766
    • (2002) Chinese J. Comput. , vol.25 , Issue.7 , pp. 759-766
    • Wang, G.1    Yu, H.2    Yang, D.3
  • 42
    • 0006679085 scopus 로고    scopus 로고
    • Some efficient algorithms for rough set methods
    • Spain
    • N.S. Hoa, Some efficient algorithms for rough set methods, in: Proceedings IPMU'96 Granada, Spain, 1996, pp. 1541-1457.
    • (1996) Proceedings IPMU'96 Granada , pp. 1541-1457
    • Hoa, N.S.1
  • 43
    • 0037734023 scopus 로고    scopus 로고
    • A new method for fast computing positive region
    • S. Liu, Q. Chen, and Z. Shi A new method for fast computing positive region Chinese J. Comput. Res. Dev. 40 5 2003 637 642
    • (2003) Chinese J. Comput. Res. Dev. , vol.40 , Issue.5 , pp. 637-642
    • Liu, S.1    Chen, Q.2    Shi, Z.3
  • 44
    • 38349018753 scopus 로고    scopus 로고
    • Quick knowledge reduction based on divide and conquer method in huge data sets
    • Springer-Verlag, Berlin, Heidelberg ISBN 3-540-77045-3, 978-3-540-77045-9
    • G. Wang, F. Hu, Quick knowledge reduction based on divide and conquer method in huge data sets, in: Proceedings of the 2nd International Conference on Pattern Recognition and Machine Intelligence, PReMI'07, Springer-Verlag, Berlin, Heidelberg, 2007, pp. 312-315. ISBN 3-540-77045-3, 978-3-540-77045-9. < http://dl.acm.org/citation.cfm?id=1781034.1781077 >.
    • (2007) Proceedings of the 2nd International Conference on Pattern Recognition and Machine Intelligence, PReMI'07 , pp. 312-315
    • Wang, G.1    Hu, F.2
  • 45
    • 17444379002 scopus 로고    scopus 로고
    • On fuzzy-rough sets approach to feature selection
    • R.B. Bhatt, and M. Gopal On fuzzy-rough sets approach to feature selection Pattern Recogn. Lett. 26 7 2005 965 975
    • (2005) Pattern Recogn. Lett. , vol.26 , Issue.7 , pp. 965-975
    • Bhatt, R.B.1    Gopal, M.2


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