메뉴 건너뛰기




Volumn 26, Issue 1, 2015, Pages 35-50

Feature selection using a neural framework with controlled redundancy

Author keywords

Dimensionality reduction; feature selection; neural network; redundancy control.

Indexed keywords

DECISION MAKING; NEURAL NETWORKS; PICKUPS; PROBLEM SOLVING; REDUNDANCY;

EID: 84919630495     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2014.2308902     Document Type: Article
Times cited : (74)

References (63)
  • 3
    • 0031078007 scopus 로고    scopus 로고
    • Feature selection: Evaluation, application, and small sample performance
    • Feb.
    • A. Jain and D. Zongker, "Feature selection: Evaluation, application, and small sample performance," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 2, pp. 153-158, Feb. 1997.
    • (1997) IEEE Trans. Pattern Anal. Mach. Intell. , vol.19 , Issue.2 , pp. 153-158
    • Jain, A.1    Zongker, D.2
  • 4
    • 0001121401 scopus 로고    scopus 로고
    • A connectionist system for feature selection
    • N. R. Pal and K. K. Chintalapudi, "A connectionist system for feature selection," Neural Parallel Sci. Comput., vol. 5, no. 3, pp. 359-381, 1997.
    • (1997) Neural Parallel Sci. Comput. , vol.5 , Issue.3 , pp. 359-381
    • Pal, N.R.1    Chintalapudi, K.K.2
  • 5
    • 77951939084 scopus 로고    scopus 로고
    • Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions
    • May
    • Y. Aksu, D. J. Miller, G. Kesidis, and Q. X. Yang, "Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions," IEEE Trans. Neural Netw., vol. 21, no. 5, pp. 701-717, May 2010.
    • (2010) IEEE Trans. Neural Netw. , vol.21 , Issue.5 , pp. 701-717
    • Aksu, Y.1    Miller, D.J.2    Kesidis, G.3    Yang, Q.X.4
  • 6
    • 49449103684 scopus 로고    scopus 로고
    • Supervised dimensionality reduction via sequential semidefinite programming
    • C. Shen, H. Li, and M. J. Brooks, "Supervised dimensionality reduction via sequential semidefinite programming," Pattern Recognit., vol. 41, no. 12, pp. 3644-3652, 2008.
    • (2008) Pattern Recognit. , vol.41 , Issue.12 , pp. 3644-3652
    • Shen, C.1    Li, H.2    Brooks, M.J.3
  • 7
    • 17044405923 scopus 로고    scopus 로고
    • Toward integrating feature selection algorithms for classification and clustering
    • Apr.
    • H. Liu and L. Yu, "Toward integrating feature selection algorithms for classification and clustering," IEEE Trans. Knowl. Data Eng., vol. 17, no. 4, pp. 491-502, Apr. 2005.
    • (2005) IEEE Trans. Knowl. Data Eng. , vol.17 , Issue.4 , pp. 491-502
    • Liu, H.1    Yu, L.2
  • 9
    • 48049087439 scopus 로고    scopus 로고
    • Feature selection with kernel class separability
    • Sep.
    • L. Wang, "Feature selection with kernel class separability," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 9, pp. 1534-1546, Sep. 2008.
    • (2008) IEEE Trans. Pattern Anal. Mach. Intell. , vol.30 , Issue.9 , pp. 1534-1546
    • Wang, L.1
  • 10
    • 0035336996 scopus 로고    scopus 로고
    • Information-theoretic algorithm for feature selection
    • May
    • M. Last, A. Kandel, and O. Maimon, "Information-theoretic algorithm for feature selection," Pattern Recognit. Lett., vol. 22, pp. 799-811, May 2001.
    • (2001) Pattern Recognit. Lett. , vol.22 , pp. 799-811
    • Last, M.1    Kandel, A.2    Maimon, O.3
  • 11
    • 40949142799 scopus 로고    scopus 로고
    • Selecting useful groups of features in a connectionist framework
    • Mar.
    • D. Chakraborty and N. R. Pal, "Selecting useful groups of features in a connectionist framework," IEEE Trans. Neural Netw., vol. 19, no. 3, pp. 381-396, Mar. 2008.
    • (2008) IEEE Trans. Neural Netw. , vol.19 , Issue.3 , pp. 381-396
    • Chakraborty, D.1    Pal, N.R.2
  • 12
    • 0035359273 scopus 로고    scopus 로고
    • Integrated feature analysis and fuzzy rule based system identification in a neuro-fuzzy paradigm
    • Jun.
    • D. Chakraborty and N. R. Pal, "Integrated feature analysis and fuzzy rule based system identification in a neuro-fuzzy paradigm," IEEE Trans. Syst. Man, Cybern. B, Cybern., vol. 31, no. 3, pp. 391-400, Jun. 2001.
    • (2001) IEEE Trans. Syst. Man, Cybern. B, Cybern. , vol.31 , Issue.3 , pp. 391-400
    • Chakraborty, D.1    Pal, N.R.2
  • 13
    • 0024895461 scopus 로고
    • A note on genetic algorithms for large-scale feature selection
    • W. Siedlick and J. Sklansky, "A note on genetic algorithms for large-scale feature selection," Pattern Recognit. Lett., vol. 10, no. 5, pp. 335-347, 1989.
    • (1989) Pattern Recognit. Lett. , vol.10 , Issue.5 , pp. 335-347
    • Siedlick, W.1    Sklansky, J.2
  • 14
    • 0002429329 scopus 로고
    • Feature selection using a multilayer perceptron
    • D. W. Ruck, S. K. Rogers, and M. Kabrisky, "Feature selection using a multilayer perceptron," J. Neural Netw., vol. 2, no. 2, pp. 40-48, 1990.
    • (1990) J. Neural Netw. , vol.2 , Issue.2 , pp. 40-48
    • Ruck, D.W.1    Rogers, S.K.2    Kabrisky, M.3
  • 15
    • 77951937407 scopus 로고    scopus 로고
    • Feature selection with redundancyconstrained class separability
    • May
    • L. Zhou, L. Wang, and C. Shen, "Feature selection with redundancyconstrained class separability," IEEE Trans. Neural Netw., vol. 21, no. 5, pp. 853-858, May 2010.
    • (2010) IEEE Trans. Neural Netw. , vol.21 , Issue.5 , pp. 853-858
    • Zhou, L.1    Wang, L.2    Shen, C.3
  • 16
    • 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., vol. 46, nos. 1-3, pp. 389-422, 2002.
    • (2002) Mach. Learn. , vol.46 , Issue.1-3 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 17
    • 34249855141 scopus 로고    scopus 로고
    • MSVM-RFE: Extensions of SVM-RFE for multiclass gene selection on DNA microarray data
    • X. Zhou and D. P. Tuck, "MSVM-RFE: Extensions of SVM-RFE for multiclass gene selection on DNA microarray data," Bioinformatics, vol. 23, no. 9, pp. 1106-1114, 2007.
    • (2007) Bioinformatics , vol.23 , Issue.9 , pp. 1106-1114
    • Zhou, X.1    Tuck, D.P.2
  • 18
    • 0000181889 scopus 로고
    • On nonlinear fractional programming
    • W. Dinkelbach, "On nonlinear fractional programming," Manag. Sci., vol. 13, no. 7, pp. 492-498, 1967.
    • (1967) Manag. Sci. , vol.13 , Issue.7 , pp. 492-498
    • Dinkelbach, W.1
  • 19
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information of criteria of max-dependency, max-relevance, and minredundancy
    • Aug.
    • H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information of criteria of max-dependency, max-relevance, and minredundancy," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 8, pp. 1226-1238, Aug. 2005.
    • (2005) IEEE Trans. Pattern Anal. Mach. Intell. , vol.27 , Issue.8 , pp. 1226-1238
    • Peng, H.1    Long, F.2    Ding, C.3
  • 20
    • 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., vol. 5, no. 10, pp. 1205-1224, 2004.
    • (2004) J. Mach. Learn. Res. , vol.5 , Issue.10 , pp. 1205-1224
    • Yu, L.1    Liu, H.2
  • 21
    • 44649105615 scopus 로고    scopus 로고
    • Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm
    • Y. Hong, S. Kwong, Y. Chang, and Q. Ren, "Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm," Pattern Recognit., vol. 41, no. 9, pp. 2742-2756, 2008.
    • (2008) Pattern Recognit. , vol.41 , Issue.9 , pp. 2742-2756
    • Hong, Y.1    Kwong, S.2    Chang, Y.3    Ren, Q.4
  • 22
    • 84972496372 scopus 로고
    • Influential observations, high leverage points, and outliers in linear regression
    • S. Chatterjee and A. S. Hadi, "Influential observations, high leverage points, and outliers in linear regression," Statist. Sci., vol. 1, no. 3, pp. 379-393, 1986.
    • (1986) Statist. Sci. , vol.1 , Issue.3 , pp. 379-393
    • Chatterjee, S.1    Hadi, A.S.2
  • 23
    • 17444406668 scopus 로고    scopus 로고
    • Identifying critical variables of principal components for unsupervised feature selection
    • Apr.
    • K. Z. Mao, "Identifying critical variables of principal components for unsupervised feature selection," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 35, no. 2, pp. 339-344, Apr. 2005.
    • (2005) IEEE Trans. Syst., Man, Cybern. B, Cybern. , vol.35 , Issue.2 , pp. 339-344
    • Mao, K.Z.1
  • 24
  • 25
  • 26
    • 27644496932 scopus 로고    scopus 로고
    • A new dependency and correlation analysis for features
    • Sep.
    • G. Qu, S. Hariri, and M. Yousif, "A new dependency and correlation analysis for features," IEEE Trans. Knowl. Data Eng., vol. 17, no. 9, pp. 1199-1207, Sep. 2005.
    • (2005) IEEE Trans. Knowl. Data Eng. , vol.17 , Issue.9 , pp. 1199-1207
    • Qu, G.1    Hariri, S.2    Yousif, M.3
  • 27
    • 77649333561 scopus 로고    scopus 로고
    • An unsupervised feature selection algorithm: Laplacian score combined with distance-based entropy measure,"
    • Nov.
    • R. Liu, N. Yang, X. Ding, and L. Ma, "An unsupervised feature selection algorithm: Laplacian score combined with distance-based entropy measure," in Proc. 3rd Int. Symp. Intell. Inf. Technol. Appl., Nov. 2009, pp. 65-68.
    • (2009) Proc. 3rd Int. Symp. Intell. Inf. Technol. Appl. , pp. 65-68
    • Liu, R.1    Yang, N.2    Ding, X.3    Ma, L.4
  • 29
    • 84864039505 scopus 로고    scopus 로고
    • Laplacian score for feature selection
    • X. He, D. Cai, and P. Niyogi, "Laplacian score for feature selection," in Proc. NIPS, 2005, p. 189.
    • (2005) Proc. NIPS , pp. 189
    • He, X.1    Cai, D.2    Niyogi, P.3
  • 30
    • 78650966380 scopus 로고    scopus 로고
    • Unsupervised feature selection for the k-means clustering problem
    • C. Boutsidis, M. W. Mahoney, and P. Drineas, "Unsupervised feature selection for the k-means clustering problem," in Proc. NIPS, 2009, pp. 153-161.
    • (2009) Proc. NIPS , pp. 153-161
    • Boutsidis, C.1    Mahoney, M.W.2    Drineas, P.3
  • 31
    • 58849086813 scopus 로고    scopus 로고
    • CUR matrix decompositions for improved data analysis
    • M. W. Mahoney and P. Drineas, "CUR matrix decompositions for improved data analysis," Proc. Nat. Acad. Sci., vol. 106, no. 3, pp. 697-702, 2009.
    • (2009) Proc. Nat. Acad. Sci. , vol.106 , Issue.3 , pp. 697-702
    • Mahoney, M.W.1    Drineas, P.2
  • 32
    • 84960463485 scopus 로고    scopus 로고
    • Minimum redundancy feature selection from microarray gene expression data
    • Aug.
    • C. Ding and H. Peng, "Minimum redundancy feature selection from microarray gene expression data," in Proc. IEEE Bioinf. Conf., Aug. 2003, pp. 523-529.
    • (2003) Proc. IEEE Bioinf. Conf. , pp. 523-529
    • Ding, C.1    Peng, H.2
  • 35
    • 84910828260 scopus 로고
    • Application of the Karhunen-Loeve expansion to feature selection and ordering
    • Apr.
    • K. Fakunaga and W. L. G. Koontz, "Application of the Karhunen-Loeve expansion to feature selection and ordering," IEEE Trans. Comput., vol. 19, no. 4, pp. 311-318, Apr. 1970.
    • (1970) IEEE Trans. Comput. , vol.19 , Issue.4 , pp. 311-318
    • Fakunaga, K.1    Koontz, W.L.G.2
  • 38
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • P. Kohavi and G. H. John, "Wrappers for feature subset selection," Artif. Intell., vol. 97, nos. 1-2, pp. 273-324, 1997.
    • (1997) Artif. Intell. , vol.97 , Issue.1-2 , pp. 273-324
    • Kohavi, P.1    John, G.H.2
  • 39
    • 31744443319 scopus 로고    scopus 로고
    • Genetic programming for simultaneous feature selection and classifier design
    • Feb.
    • D. P. Muni, N. R. Pal, and J. Das, "Genetic programming for simultaneous feature selection and classifier design," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 36, no. 1, pp. 106-117, Feb. 2006.
    • (2006) IEEE Trans. Syst., Man, Cybern. B, Cybern. , vol.36 , Issue.1 , pp. 106-117
    • Muni, D.P.1    Pal, N.R.2    Das, J.3
  • 40
    • 0036601484 scopus 로고    scopus 로고
    • Fuzzy logic approaches to structure preserving dimensionality reduction
    • Jun.
    • N. R. Pal, "Fuzzy logic approaches to structure preserving dimensionality reduction," IEEE Trans. Fuzzy Syst., vol. 10, no. 3, pp. 277-286, Jun. 2002.
    • (2002) IEEE Trans. Fuzzy Syst. , vol.10 , Issue.3 , pp. 277-286
    • Pal, N.R.1
  • 41
    • 0033751612 scopus 로고    scopus 로고
    • Unsupervised feature evaluation: A neuro-fuzzy approach
    • Mar.
    • S. K. Pal, R. K. De, and J. Basak, "Unsupervised feature evaluation: A neuro-fuzzy approach," IEEE Trans. Neural Netw., vol. 11, no. 2, pp. 366-376, Mar. 2000.
    • (2000) IEEE Trans. Neural Netw. , vol.11 , Issue.2 , pp. 366-376
    • Pal, S.K.1    De, R.K.2    Basak, J.3
  • 42
    • 0000903874 scopus 로고    scopus 로고
    • Soft computing for feature analysis
    • N. R. Pal, "Soft computing for feature analysis," Fuzzy Sets Syst., vol. 103, no. 2, pp. 201-221, 1999.
    • (1999) Fuzzy Sets Syst. , vol.103 , Issue.2 , pp. 201-221
    • Pal, N.R.1
  • 43
    • 2442612917 scopus 로고    scopus 로고
    • A novel approach for designing classifiers using genetic programming
    • Apr.
    • D. P. Muni, N. R. Pal, and J. Das, "A novel approach for designing classifiers using genetic programming," IEEE Trans. Evol. Comput., vol. 8, no. 2, pp. 183-196, Apr. 2004.
    • (2004) IEEE Trans. Evol. Comput. , vol.8 , Issue.2 , pp. 183-196
    • Muni, D.P.1    Pal, N.R.2    Das, J.3
  • 44
    • 0015127383 scopus 로고
    • Feature selector with a linear dependence measure
    • Sep.
    • S. K. Das, "Feature selector with a linear dependence measure," IEEE Trans. Comput., vol. 20, no. 9, pp. 1106-1109, Sep. 1971.
    • (1971) IEEE Trans. Comput. , vol.20 , Issue.9 , pp. 1106-1109
    • Das, S.K.1
  • 45
    • 75449099314 scopus 로고    scopus 로고
    • Laplacian linear discriminant analysis approach to unsupervised feature selection
    • Dec.
    • S. Nijima and Y. Okuno, "Laplacian linear discriminant analysis approach to unsupervised feature selection," IEEE/ACM Trans. Comput. Biol. Bioinf., vol. 6, no. 4, pp. 605-614, Dec. 2009.
    • (2009) IEEE/ACM Trans. Comput. Biol. Bioinf. , vol.6 , Issue.4 , pp. 605-614
    • Nijima, S.1    Okuno, Y.2
  • 46
    • 33645342233 scopus 로고    scopus 로고
    • On identifying marker genes from gene expression data in a neural framework through online feature analysis
    • Apr.
    • N. R. Pal, A. Sharma, S. Sanadhya, and Karmeshu, "On identifying marker genes from gene expression data in a neural framework through online feature analysis," Int. J. Intell. Syst., vol. 21, no. 4, pp. 453-467, Apr. 2006.
    • (2006) Int. J. Intell. Syst. , vol.21 , Issue.4 , pp. 453-467
    • Pal, N.R.1    Sharma, A.2    Sanadhya, S.3    Karmeshu4
  • 47
    • 3042810113 scopus 로고    scopus 로고
    • Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification
    • Dec.
    • C. D. Huang, C. T. Lin, and N. R. Pal, "Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification," IEEE Trans. Nanobiosci., vol. 2, no. 4, pp. 221-232, Dec. 2003.
    • (2003) IEEE Trans. Nanobiosci. , vol.2 , Issue.4 , pp. 221-232
    • Huang, C.D.1    Lin, C.T.2    Pal, N.R.3
  • 48
    • 0035245294 scopus 로고    scopus 로고
    • A new approach to target recognition for LADAR data
    • Feb.
    • N. R. Pal, T. Cahoon, J. C. Bezdek, and K. Pal, "A new approach to target recognition for LADAR data," IEEE Trans. Fuzzy Syst., vol. 9, no. 1, pp. 44-52, Feb. 2001.
    • (2001) IEEE Trans. Fuzzy Syst. , vol.9 , Issue.1 , pp. 44-52
    • Pal, N.R.1    Cahoon, T.2    Bezdek, J.C.3    Pal, K.4
  • 51
    • 84865063360 scopus 로고    scopus 로고
    • Redundancy-constrained feature selection with radial basis function networks
    • Jun.
    • N. R. Pal and M. Malpani, "Redundancy-constrained feature selection with radial basis function networks," in Proc. IJCNN, Jun. 2012, pp. 1-8.
    • (2012) Proc. IJCNN , pp. 1-8
    • Pal, N.R.1    Malpani, M.2
  • 52
    • 84886567160 scopus 로고    scopus 로고
    • [online]. Available
    • (2012). UCI Machine Learning Repository [online]. Available: http://archive.ics.uci.edu/ml/datasets.html
    • (2012) UCI Machine Learning Repository
  • 53
    • 77950210130 scopus 로고    scopus 로고
    • Accurate telemonitoring of Parkinson's disease progression by noninvasive speech tests
    • Apr.
    • A. Tsanas, M. A. Little, P. E. McSharry, and L. O. Ramig, "Accurate telemonitoring of Parkinson's disease progression by noninvasive speech tests," IEEE Trans. Biomed. Eng., vol. 57, no. 4, pp. 884-893, Apr. 2010.
    • (2010) IEEE Trans. Biomed. Eng. , vol.57 , Issue.4 , pp. 884-893
    • Tsanas, A.1    Little, M.A.2    McSharry, P.E.3    Ramig, L.O.4
  • 54
    • 84870441851 scopus 로고    scopus 로고
    • A fast clustering-based feature subset selection algorithm for high-dimensional data
    • Jan.
    • Q. Song, J. Ni, and G. Wang, "A fast clustering-based feature subset selection algorithm for high-dimensional data," IEEE Trans. Knowl. Data Eng., vol. 25, no. 1, pp. 1-14, Jan. 2013.
    • (2013) IEEE Trans. Knowl. Data Eng. , vol.25 , Issue.1 , pp. 1-14
    • Song, Q.1    Ni, J.2    Wang, G.3
  • 56
    • 84881041271 scopus 로고    scopus 로고
    • 2,1-norm regularized discriminative feature selection for unsupervised learning
    • Y. Yang, H. T. Shen, Z. Ma, Z. Huang, and X. Zhou, "2,1-norm regularized discriminative feature selection for unsupervised learning," in Proc. 22nd Int. Joint Conf. Artif. Intell., vol. 2. 2011, pp. 1589-1594.
    • (2011) Proc. 22nd Int. Joint Conf. Artif. Intell. , vol.2 , pp. 1589-1594
    • Yang, Y.1    Shen, H.T.2    Ma, Z.3    Huang, Z.4    Zhou, X.5
  • 58
    • 85167396596 scopus 로고    scopus 로고
    • Unsupervised feature selection using nonnegative spectral analysis
    • Z. Li, Y. Yang, J. Liu, X. Zhou, and H. Lu, "Unsupervised feature selection using nonnegative spectral analysis," in Proc. AAAI Conf. Artif. Intell., 2012, pp. 1-7.
    • (2012) Proc. AAAI Conf. Artif. Intell. , pp. 1-7
    • Li, Z.1    Yang, Y.2    Liu, J.3    Zhou, X.4    Lu, H.5
  • 59
    • 80555129673 scopus 로고    scopus 로고
    • Structured variable selection with sparsity-inducing norms
    • Feb.
    • R. Jenatton, J.-Y. Audibert, and F. Bach, "Structured variable selection with sparsity-inducing norms," J. Mach. Learn. Res., vol. 12, pp. 2777-2824, Feb. 2011.
    • (2011) J. Mach. Learn. Res. , vol.12 , pp. 2777-2824
    • Jenatton, R.1    Audibert, J.-Y.2    Bach, F.3
  • 60
    • 0034244751 scopus 로고    scopus 로고
    • Normalized cuts and image segmentation
    • Aug.
    • J. Shi and J. Malik, "Normalized cuts and image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 8, pp. 888-905, Aug. 2000.
    • (2000) IEEE Trans. Pattern Anal. Mach. Intell. , vol.22 , Issue.8 , pp. 888-905
    • Shi, J.1    Malik, J.2
  • 61
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • S. Dudoit, J. Fridlyand, and T. P. Speed, "Comparison of discrimination methods for the classification of tumors using gene expression data," J. Amer. Statist. Assoc., vol. 97, no. 457, pp. 77-87, 2002.
    • (2002) J. Amer. Statist. Assoc. , vol.97 , Issue.457 , pp. 77-87
    • Dudoit, S.1    Fridlyand, J.2    Speed, T.P.3
  • 62
    • 77955405900 scopus 로고    scopus 로고
    • Feature selection guided by structural information
    • M. Slawski, W. zu Castell, and G. Tutz, "Feature selection guided by structural information," Ann. Appl. Statist., vol. 4, no. 2, pp. 1056-1080, 2010.
    • (2010) Ann. Appl. Statist. , vol.4 , Issue.2 , pp. 1056-1080
    • Slawski, M.1    Castell Zu, W.2    Tutz, G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.