메뉴 건너뛰기




Volumn , Issue , 2007, Pages 214-221

Fuzzy c-means classifier with deterministic initialization and missing value imputation

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); OPTIMIZATION; PARAMETER ESTIMATION; RANDOM PROCESSES;

EID: 34548850863     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FOCI.2007.372171     Document Type: Conference Paper
Times cited : (13)

References (30)
  • 2
    • 84946263679 scopus 로고
    • Robust regression using iteratively reweighted least-squares
    • P. W. Holland and R. E. Welsch, "Robust regression using iteratively reweighted least-squares, "Communications in Statistics, vol. A6, no. 9, pp. 813-827, 1977.
    • (1977) Communications in Statistics , vol.A6 , Issue.9 , pp. 813-827
    • Holland, P.W.1    Welsch, R.E.2
  • 7
    • 34249753618 scopus 로고
    • Support-vector network
    • C. Cortes and V. Vapnik, "Support-vector network." Machine Learning, vol.20, pp.273-297, 1995.
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 10
    • 25844469288 scopus 로고    scopus 로고
    • The nearest sub-class classifier: A compromise between the nearest mean and nearest neighbor classifier
    • C.J. Veenman and M.J.T. Reinders, "The nearest sub-class classifier: a compromise between the nearest mean and nearest neighbor classifier," IEEE Transactions on PAMI, vol.27, no.9, pp.1417-1429, 2005.
    • (2005) IEEE Transactions on PAMI , vol.27 , Issue.9 , pp. 1417-1429
    • Veenman, C.J.1    Reinders, M.J.T.2
  • 12
    • 0028497290 scopus 로고
    • Maximum likelihood training of probabilistic neural networks
    • R. L. Streit and T. E. Luginbuhl, "Maximum likelihood training of probabilistic neural networks," IEEE Transactions on Neural Networks, vol.5, no.5, pp.764-783, 1994.
    • (1994) IEEE Transactions on Neural Networks , vol.5 , Issue.5 , pp. 764-783
    • Streit, R.L.1    Luginbuhl, T.E.2
  • 14
    • 0034960264 scopus 로고    scopus 로고
    • Missing value estimation methods for dna microarrays
    • O. Troyanskaya, et.al., "Missing value estimation methods for dna microarrays," Bioinformatics, vol.17, no.6, pp.520-525, 2001.
    • (2001) Bioinformatics , vol.17 , Issue.6 , pp. 520-525
    • Troyanskaya, O.1
  • 15
    • 0018656141 scopus 로고
    • Pattern recognition with partly missing data
    • J. K. Dixon, "Pattern recognition with partly missing data," IEEE Transactions on Systems, Man, and Cybernetics, vol.SMC-9, no. 10, pp.617-621, 1979.
    • (1979) IEEE Transactions on Systems, Man, and Cybernetics , vol.SMC-9 , Issue.10 , pp. 617-621
    • Dixon, J.K.1
  • 17
    • 1942532746 scopus 로고    scopus 로고
    • Linear fuzzy clustering techniques with missing values and their application to local principal component analysis
    • K. Honda, H. Ichihashi, "Linear fuzzy clustering techniques with missing values and their application to local principal component analysis," IEEE Trans. Fuzzy Syst., vol.12, no.2, pp.183-193, 2004.
    • (2004) IEEE Trans. Fuzzy Syst , vol.12 , Issue.2 , pp. 183-193
    • Honda, K.1    Ichihashi, H.2
  • 18
    • 3943049970 scopus 로고    scopus 로고
    • Component-wise robust linear fuzzy clustering for collaborative filtering
    • K. Honda, H. Ichihashi, "Component-wise robust linear fuzzy clustering for collaborative filtering," Int. J. Approximate Reasoning., vol.37, no.2, pp. 127-144, 2004.
    • (2004) Int. J. Approximate Reasoning , vol.37 , Issue.2 , pp. 127-144
    • Honda, K.1    Ichihashi, H.2
  • 19
    • 26944478789 scopus 로고    scopus 로고
    • Methods of fuzzy c-means and possibilistic clustering using a quadratic term
    • S. Miyamoto, D. Suizu, O. Takata, "Methods of fuzzy c-means and possibilistic clustering using a quadratic term, Scientiae Mathematicae Japonicae vol.60, no.2, pp.217-233, 2004.
    • (2004) Scientiae Mathematicae Japonicae , vol.60 , Issue.2 , pp. 217-233
    • Miyamoto, S.1    Suizu, D.2    Takata, O.3
  • 21
    • 0018057468 scopus 로고
    • Fuzzy clustering with a fuzzy covariance matrix
    • D. E. Gustafson and W. C. Kessel, "Fuzzy clustering with a fuzzy covariance matrix, "Proc. IEEE CDC, vol.2, pp.761-766, 1979.
    • (1979) Proc. IEEE CDC , vol.2 , pp. 761-766
    • Gustafson, D.E.1    Kessel, W.C.2
  • 22
    • 0032595185 scopus 로고    scopus 로고
    • Alternating cluster estimation: A new tool for clustering and function approximation
    • T. A. Runkler and J. C. Bezdek, "Alternating cluster estimation: a new tool for clustering and function approximation," IEEE Trans. Fuzzy Syst., vol. 7, no. 4, pp. 377-393, 1999.
    • (1999) IEEE Trans. Fuzzy Syst , vol.7 , Issue.4 , pp. 377-393
    • Runkler, T.A.1    Bezdek, J.C.2
  • 23
  • 24
    • 0033556788 scopus 로고    scopus 로고
    • Mixtures of probabilistic principal component analysers
    • M.E. Tipping and CM. Bishop, "Mixtures of probabilistic principal component analysers, "Neural Computation, vol.11, pp.443-482, 1999.
    • (1999) Neural Computation , vol.11 , pp. 443-482
    • Tipping, M.E.1    Bishop, C.M.2
  • 25
    • 0030143221 scopus 로고    scopus 로고
    • Precise selection of candidates for hand written character recognition
    • F. Sun, S.Omachi, and H. Aso, "Precise selection of candidates for hand written character recognition," IEICE Trans. Information and Systems, vol.E79-D, no.3, pp.510-515, 1996
    • (1996) IEICE Trans. Information and Systems , vol.E79-D , Issue.3 , pp. 510-515
    • Sun, F.1    Omachi, S.2    Aso, H.3
  • 27
    • 0002714543 scopus 로고    scopus 로고
    • Making large-scale SVM learning practical
    • B. Scholkopf et al.ed, MIT Press, Cambridge, pp
    • T. Joachims, "Making large-scale SVM learning practical," In: B. Scholkopf et al.(ed.). Advances in Kernel Methods: Support Vector Learning, MIT Press, Cambridge, pp. 169-184, 1999.
    • (1999) Advances in Kernel Methods: Support Vector Learning , pp. 169-184
    • Joachims, T.1
  • 28
    • 0035575921 scopus 로고    scopus 로고
    • Nearest prototype classifier designs: An experimental study
    • J. C. Bezdek and L. I. Kuncheva, "Nearest prototype classifier designs: An experimental study," Int. J. of Intelligent Systems, vol.16, pp. 1445-1473, 2001.
    • (2001) Int. J. of Intelligent Systems , vol.16 , pp. 1445-1473
    • Bezdek, J.C.1    Kuncheva, L.I.2
  • 29
    • 0032595775 scopus 로고    scopus 로고
    • General and efficient multisplitting of numerical attributes
    • T. Elomaa and J. Rousu, "General and efficient multisplitting of numerical attributes,"Machine Learning, vol. 36, no. 3, pp. 201-244, 1999.
    • (1999) Machine Learning , vol.36 , Issue.3 , pp. 201-244
    • Elomaa, T.1    Rousu, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.