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Volumn 3040, Issue , 2004, Pages 618-627

Using the geometrical distribution of prototypes for training set condensing

Author keywords

[No Author keywords available]

Indexed keywords

TECHNOLOGY TRANSFER; ALGORITHMS; DATA REDUCTION; GEOMETRY;

EID: 7444264764     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-25945-9_61     Document Type: Conference Paper
Times cited : (11)

References (16)
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    • (1991) Machine Learning , vol.6 , Issue.1 , pp. 37-66
    • Aha, D.W.1    Kibler, D.2    Albert, M.K.3
  • 3
    • 0016127071 scopus 로고
    • Finding prototypes for nearest neighbor classifiers
    • C.L. Chang. Finding prototypes for nearest neighbor classifiers. IEEE Trans. on Computers, 23:1179–1184, 1974.
    • (1974) IEEE Trans. On Computers , vol.23 , pp. 1179-1184
    • Chang, C.L.1
  • 5
    • 0029669422 scopus 로고    scopus 로고
    • A new definition of neighbourhood of a point in multi-dimensional space
    • B.B. Chaudhuri. A new definition of neighbourhood of a point in multi-dimensional space. Pattern Recognition Letters, 17:11–17, 1996.
    • (1996) Pattern Recognition Letters , vol.17 , pp. 11-17
    • Chaudhuri, B.B.1
  • 6
    • 0030196853 scopus 로고    scopus 로고
    • A sample set condensation algorithm for the class sensitive artificial neural network
    • C.H. Chen and A. Józwik. A sample set condensation algorithm for the class sensitive artificial neural network. Pattern Recognition Letters, 17:819–823, 1996.
    • (1996) Pattern Recognition Letters , vol.17 , pp. 819-823
    • Chen, C.H.1    Józwik, A.2
  • 8
    • 0028385080 scopus 로고
    • Minimal consistent subset (MCS) identification for optimal nearest neighbor decision systems design
    • B.V. Dasarathy. Minimal consistent subset (MCS) identification for optimal nearest neighbor decision systems design. IEEE Trans. on Systems, Man, and Cybernetics, 24:511–517, 1994.
    • (1994) IEEE Trans. On Systems, Man, and Cybernetics , vol.24 , pp. 511-517
    • Dasarathy, B.V.1
  • 10
    • 84931162639 scopus 로고
    • The condensed nearest neighbor rule
    • P. Hart. The condensed nearest neighbor rule. IEEE Trans. on Information Theory, 14:505–516, 1968.
    • (1968) IEEE Trans. On Information Theory , vol.14 , pp. 505-516
    • Hart, P.1
  • 12
    • 0031273787 scopus 로고    scopus 로고
    • On the use of neighbourhood-based nonparametric classifiers
    • J.S. Sánchez, F. Pla, and F.J. Ferri. On the use of neighbourhood-based nonparametric classifiers. Pattern Recognition Letters, 18:1179–1186, 1997.
    • (1997) Pattern Recognition Letters , vol.18 , pp. 1179-1186
    • Sánchez, J.S.1    Pla, F.2    Ferri, F.J.3
  • 15
    • 0015361129 scopus 로고
    • Asymptotic properties of nearest neighbor rules using edited data sets
    • D.L. Wilson. Asymptotic properties of nearest neighbor rules using edited data sets. IEEE Trans. on Systems, Man and Cybernetics, 2:408–421, 1972.
    • (1972) IEEE Trans. On Systems, Man and Cybernetics , vol.2 , pp. 408-421
    • Wilson, D.L.1
  • 16
    • 0343081513 scopus 로고    scopus 로고
    • Reduction techniques for instance-based learning algorithms
    • D.R. Wilson and T.R. Martinez. Reduction techniques for instance-based learning algorithms. Machine Learning, 38:257–286, 2000.
    • (2000) Machine Learning , vol.38 , pp. 257-286
    • Wilson, D.R.1    Martinez, T.R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.