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Volumn 10, Issue 3, 2015, Pages 52-60

ENN: Extended Nearest Neighbor Method for Pattern Recognition [Research Frontier]

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; NEAREST NEIGHBOR SEARCH;

EID: 84937796378     PISSN: 1556603X     EISSN: None     Source Type: Journal    
DOI: 10.1109/MCI.2015.2437512     Document Type: Article
Times cited : (113)

References (40)
  • 2
    • 84892771609 scopus 로고    scopus 로고
    • Nature [Online]. Available:
    • Nature. (2008). Big data. [Online]. Available: http://www.nature.com/news/specials/bigdata/index.html
    • (2008) Big Data
  • 3
    • 84908019121 scopus 로고    scopus 로고
    • Big data opportunities and challenges: Discussions from data analytics perspectives
    • Z. Zhou, N. Chawla, Y. Jin, and G. Williams, "Big data opportunities and challenges: Discussions from data analytics perspectives, " IEEE Comput. Intell. Mag., vol. 9, no. 4, pp. 62-74, 2014.
    • (2014) IEEE Comput. Intell. Mag. , vol.9 , Issue.4 , pp. 62-74
    • Zhou, Z.1    Chawla, N.2    Jin, Y.3    Williams, G.4
  • 4
    • 84904651375 scopus 로고    scopus 로고
    • The emerging big dimensionality
    • Y. Zhai, Y. Ong, and I. Tsang, "The emerging big dimensionality, " IEEE Comput. Intell. Mag., vol. 9, no. 3, pp. 14-26, 2014.
    • (2014) IEEE Comput. Intell. Mag. , vol.9 , Issue.3 , pp. 14-26
    • Zhai, Y.1    Ong, Y.2    Tsang, I.3
  • 5
    • 0003909532 scopus 로고
    • Discriminatory analysisnonparametric discrimination: Consistency properties
    • Randolph Field, Texas, Project 21-49-004, Tech. Rep.
    • E. Fix and J. L. Hodges Jr, "Discriminatory analysisnonparametric discrimination: Consistency properties, " U.S. Air Force Sch. Aviation Medicine, Randolph Field, Texas, Project 21-49-004, Tech. Rep. 4, 1951.
    • (1951) U.S. Air Force Sch. Aviation Medicine , vol.4
    • Fix, E.1    Hodges, J.L.2
  • 6
    • 84926662675 scopus 로고
    • Nearest neighbor pattern classification
    • T. Cover and P. Hart, "Nearest neighbor pattern classification, " IEEE Trans. Inform. Theory, vol. 13, no. 1, pp. 21-27, 1967.
    • (1967) IEEE Trans. Inform. Theory , vol.13 , Issue.1 , pp. 21-27
    • Cover, T.1    Hart, P.2
  • 7
    • 0030624540 scopus 로고    scopus 로고
    • Better prediction of protein cellular localization sites with the k nearest neighbors classifier
    • P. Horton and K. Nakai, "Better prediction of protein cellular localization sites with the k nearest neighbors classifier, " in Proc. 5th Int. Conf. Intelligent Systems Molecular Biology, 1997, vol. 5, pp. 147-152.
    • (1997) Proc. 5th Int. Conf. Intelligent Systems Molecular Biology , vol.5 , pp. 147-152
    • Horton, P.1    Nakai, K.2
  • 10
    • 0000581356 scopus 로고
    • An introduction to kernel and nearest-neighbor nonparametric regression
    • N. S. Altman, "An introduction to kernel and nearest-neighbor nonparametric regression, " Amer. Stat., vol. 46, no. 3, pp. 175-185, 1992.
    • (1992) Amer. Stat. , vol.46 , Issue.3 , pp. 175-185
    • Altman, N.S.1
  • 11
    • 21144472623 scopus 로고
    • Variable kernel density estimation
    • G. R. Terrell and D. W. Scott, "Variable kernel density estimation, " Ann. Stat., vol. 20, no. 3, pp. 1236-1265, 1992.
    • (1992) Ann. Stat. , vol.20 , Issue.3 , pp. 1236-1265
    • Terrell, G.R.1    Scott, D.W.2
  • 12
    • 0039253819 scopus 로고    scopus 로고
    • LOF: Identifying density-based local outliers
    • M. M. Breunig, H.-P. Kriegel, R. T. Ng, and J. Sander, "LOF: Identifying density-based local outliers, " ACM SIGMOD Rec., vol. 29, no. 2, pp. 93-104, 2000.
    • (2000) ACM SIGMOD Rec. , vol.29 , Issue.2 , pp. 93-104
    • Breunig, M.M.1    Kriegel, H.-P.2    Ng, R.T.3    Sander, J.4
  • 14
    • 85164392958 scopus 로고
    • A study of cross-validation and bootstrap for accuracy estimation and model selection
    • R. Kohavi, "A study of cross-validation and bootstrap for accuracy estimation and model selection, " in Proc. Int. Joint Conf. Artificial Intelligence, vol. 14, pp. 1137-1145, 1995.
    • (1995) Proc. Int. Joint Conf. Artificial Intelligence , vol.14 , pp. 1137-1145
    • Kohavi, R.1
  • 17
    • 61749090884 scopus 로고    scopus 로고
    • Distance metric learning for large margin nearest neighbor classification
    • Feb.
    • K. Q. Weinberger and L. K. Saul, "Distance metric learning for large margin nearest neighbor classification, " J. Machine Learn. Res., vol. 10, pp. 207-244, Feb. 2009.
    • (2009) J. Machine Learn. Res. , vol.10 , pp. 207-244
    • Weinberger, K.Q.1    Saul, L.K.2
  • 19
    • 33750796974 scopus 로고    scopus 로고
    • Improving nearest neighbor rule with a simple adaptive distance measure
    • J. Wang, P. Neskovic, and L. N. Cooper, "Improving nearest neighbor rule with a simple adaptive distance measure, " Pattern Recognit. Lett., vol. 28, no. 2, pp. 207-213, 2007.
    • (2007) Pattern Recognit. Lett. , vol.28 , Issue.2 , pp. 207-213
    • Wang, J.1    Neskovic, P.2    Cooper, L.N.3
  • 20
    • 84897087959 scopus 로고    scopus 로고
    • A survey on metric learning for feature vectors and structured data
    • To be published
    • A. Bellet, A. Habrard, and M. Sebban, "A survey on metric learning for feature vectors and structured data, " Comput. Res. Repository, 2013, to be published.
    • (2013) Comput. Res. Repository
    • Bellet, A.1    Habrard, A.2    Sebban, M.3
  • 21
    • 0030164799 scopus 로고    scopus 로고
    • Discriminant adaptive nearest neighbor classification
    • T. Hastie and R. Tibshirani, "Discriminant adaptive nearest neighbor classification, " IEEE Trans. Pattern Anal. Machine Intell., vol. 18, no. 6, pp. 607-616, 1996.
    • (1996) IEEE Trans. Pattern Anal. Machine Intell. , vol.18 , Issue.6 , pp. 607-616
    • Hastie, T.1    Tibshirani, R.2
  • 22
    • 0018492515 scopus 로고
    • The condensed nearest neighbor rule using the concept of mutual nearest neighborhood
    • K. C. Gowda and G. Krishna, "The condensed nearest neighbor rule using the concept of mutual nearest neighborhood, " IEEE Trans. Inform. Theory, vol. 25, no. 4, pp. 488-490, 1979.
    • (1979) IEEE Trans. Inform. Theory , vol.25 , Issue.4 , pp. 488-490
    • Gowda, K.C.1    Krishna, G.2
  • 23
    • 0037209504 scopus 로고    scopus 로고
    • Breast cancer detection using rank nearest neighbor classification rules
    • S. C. Bagui, S. Bagui, K. Pal, and N. R. Pal, "Breast cancer detection using rank nearest neighbor classification rules, " Pattern Recognit., vol. 36, no. 1, pp. 25-34, 2003.
    • (2003) Pattern Recognit , vol.36 , Issue.1 , pp. 25-34
    • Bagui, S.C.1    Bagui, S.2    Pal, K.3    Pal, N.R.4
  • 24
    • 84945709355 scopus 로고
    • An algorithm for finding best matches in logarithmic expected time
    • J. H. Friedman, J. L. Bentley, and R. A. Finkel, "An algorithm for finding best matches in logarithmic expected time, " ACM Trans. Math. Softw., vol. 3, no. 3, pp. 209-226, 1977.
    • (1977) ACM. Trans. Math. Softw. , vol.3 , Issue.3 , pp. 209-226
    • Friedman, J.H.1    Bentley, J.L.2    Finkel, R.A.3
  • 25
    • 0001020875 scopus 로고    scopus 로고
    • Performance evaluation of the nearest feature line method in image classification and retrieval
    • S. Z. Li, K. L. Chan, and C. Wang, "Performance evaluation of the nearest feature line method in image classification and retrieval, " IEEE Trans. Pattern Anal. Machine Intell., vol. 22, no. 11, pp. 1335-1349, 2000.
    • (2000) IEEE Trans. Pattern Anal. Machine Intell. , vol.22 , Issue.11 , pp. 1335-1349
    • Li, S.Z.1    Chan, K.L.2    Wang, C.3
  • 26
    • 0035441284 scopus 로고    scopus 로고
    • A fast nearest-neighbor algorithm based on a principal axis search tree
    • J. McNames, "A fast nearest-neighbor algorithm based on a principal axis search tree, " IEEE Trans. Pattern Anal. Machine Intell., vol. 23, no. 9, pp. 964-976, 2001.
    • (2001) IEEE Trans. Pattern Anal. Machine Intell. , vol.23 , Issue.9 , pp. 964-976
    • McNames, J.1
  • 27
    • 33745369515 scopus 로고    scopus 로고
    • New algorithms for efficient high-dimensional nonparametric classification
    • T. Liu, A. W. Moore, and A. Gray, "New algorithms for efficient high-dimensional nonparametric classification, " J. Machine Learn. Res., vol. 7, pp. 1135-1158, 2006.
    • (2006) J. Machine Learn. Res. , vol.7 , pp. 1135-1158
    • Liu, T.1    Moore, A.W.2    Gray, A.3
  • 29
    • 0031644241 scopus 로고    scopus 로고
    • Approximate nearest neighbors: Towards removing the curse of dimensionality
    • P. Indyk and R. Motwani, "Approximate nearest neighbors: Towards removing the curse of dimensionality, " in Proc. 30th Annu. ACM Symp. Theory Computing, 1998, pp. 604-613.
    • (1998) Proc. 30th Annu. ACM Symp. Theory Computing , pp. 604-613
    • Indyk, P.1    Motwani, R.2
  • 30
    • 68549133155 scopus 로고    scopus 로고
    • Learning from imbalanced data
    • H. He and E. A. Garcia, "Learning from imbalanced data, " IEEE Trans. Know. Data Eng., vol. 21, no. 9, pp. 1263-1284, 2009.
    • (2009) IEEE Trans. Know. Data Eng. , vol.21 , Issue.9 , pp. 1263-1284
    • He, H.1    Garcia, E.A.2
  • 32
    • 0000474812 scopus 로고
    • Multivariate two-sample tests based on nearest neighbors
    • M. F. Schilling, "Multivariate two-sample tests based on nearest neighbors, " J. Amer. Stat. Assoc., vol. 81, no. 395, pp. 799-806, 1986.
    • (1986) J. Amer. Stat. Assoc. , vol.81 , Issue.395 , pp. 799-806
    • Schilling, M.F.1
  • 33
    • 0011474810 scopus 로고
    • Mutual and shared neighbor probabilities: Finite-and infinite-dimensional results
    • M. Schilling, "Mutual and shared neighbor probabilities: Finite-and infinite-dimensional results, " Adv. Appl. Probab., vol. 18, no. 2, pp. 388-405, 1986.
    • (1986) Adv. Appl. Probab. , vol.18 , Issue.2 , pp. 388-405
    • Schilling, M.1
  • 34
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradient-based learning applied to document recognition, " Proc. IEEE, vol. 86, no. 11, pp. 2278-2324, 1998.
    • (1998) Proc. IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 37
    • 77957793322 scopus 로고    scopus 로고
    • RAMOBoost: Ranked minority over-sampling in boosting
    • S. Chen, H. He, and E. A. Garcia, "RAMOBoost: Ranked minority over-sampling in boosting, " IEEE Trans. Neural Networks, vol. 21, no. 10, pp. 1624-1642, 2010.
    • (2010) IEEE Trans. Neural Networks , vol.21 , Issue.10 , pp. 1624-1642
    • Chen, S.1    He, H.2    Garcia, E.A.3
  • 38
    • 79961009224 scopus 로고    scopus 로고
    • A weighted k-nearest neighbor density estimate for geometric inference
    • G. Biau, F. Chazal, D. Cohen-Steiner, L. Devroye, and C. Rodriguez, "A weighted k-nearest neighbor density estimate for geometric inference, " Electron. J. Stat., vol. 5, pp. 204-237, 2011.
    • Electron. J. Stat. , vol.5 , Issue.2011 , pp. 204-237
    • Biau, G.1    Chazal, F.2    Cohen-Steiner, D.3    Devroye, L.4    Rodriguez, C.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.