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Volumn 3070, Issue , 2004, Pages 580-585

Comparison of instance selection algorithms II. results and comments

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; DATABASE SYSTEMS; LEARNING SYSTEMS; NEURAL NETWORKS; STANDARDIZATION; TREES (MATHEMATICS); TUMORS;

EID: 9444268167     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24844-6_87     Document Type: Conference Paper
Times cited : (90)

References (15)
  • 1
    • 0015361129 scopus 로고
    • Asymptotic properties of nearest neighbor rules using edited data
    • Wilson, D.: Asymptotic properties of nearest neighbor rules using edited data. IEEE Transactions on Systems, Man, and Cybernetics 2 (1972) 408-421
    • (1972) IEEE Transactions on Systems, Man, and Cybernetics , vol.2 , pp. 408-421
    • Wilson, D.1
  • 3
    • 9444255746 scopus 로고    scopus 로고
    • Data regularization
    • Rutkowski, L., Tadeusiewicz, R., eds., Zakopane, Poland
    • Jankowski, N.: Data regularization. In Rutkowski, L., Tadeusiewicz, R., eds.: Neural Networks and Soft Computing, Zakopane, Poland (2000) 209-214
    • (2000) Neural Networks and Soft Computing , pp. 209-214
    • Jankowski, N.1
  • 5
    • 0016127071 scopus 로고
    • Finding prototypes for nearest neighbor classifiers
    • Chang, C.L.: Finding prototypes for nearest neighbor classifiers. IEEE Transactions on Computers 23 (1974) 1179-1184
    • (1974) IEEE Transactions on Computers , vol.23 , pp. 1179-1184
    • Chang, C.L.1
  • 9
    • 0036104537 scopus 로고    scopus 로고
    • Advances in instance selection for instance-based learning algorithms
    • Brighton, H., Mellish, C.: Advances in instance selection for instance-based learning algorithms. Data Mining and Knowledge Discovery 6 (2002) 153-172
    • (2002) Data Mining and Knowledge Discovery , vol.6 , pp. 153-172
    • Brighton, H.1    Mellish, C.2
  • 10
    • 0343081513 scopus 로고    scopus 로고
    • Reduction techniques for instance-based learning algorithms
    • Wilson, D.R., Martinez, T.R.: Reduction techniques for instance-based learning algorithms. Machine Learning 38 (2000) 257-286
    • (2000) Machine Learning , vol.38 , pp. 257-286
    • Wilson, D.R.1    Martinez, T.R.2
  • 11
    • 0003505613 scopus 로고
    • Learning vector quantization for pattern recognition
    • Helsinki University of Technology, Espoo, Finland
    • Kohonen, T.: Learning vector quantization for pattern recognition. Technical Report TKK-F-A601, Helsinki University of Technology, Espoo, Finland (1986)
    • (1986) Technical Report , vol.TKK-F-A601
    • Kohonen, T.1
  • 12
    • 0012657799 scopus 로고
    • Prototype and feature selection by sampling and random mutation hill climbing algorithms
    • Skalak, D.B.: Prototype and feature selection by sampling and random mutation hill climbing algorithms. In: International Conference on Machine Learning. (1994) 293-301
    • (1994) International Conference on Machine Learning , pp. 293-301
    • Skalak, D.B.1
  • 15
    • 9444229913 scopus 로고    scopus 로고
    • From research on a new method of development of quasi-optimal decision trees
    • Kopotek, M., Michalewicz, M., Wierzcho, S.T., eds.: Warszawa, Institute of computer science
    • Hippe, Z.S., Iwaszek, G.: From research on a new method of development of quasi-optimal decision trees. In Kopotek, M., Michalewicz, M., Wierzcho, S.T., eds.: Intelligent Information Systems IX, Warszawa, Institute of computer science (2000) 31-35
    • (2000) Intelligent Information Systems IX , pp. 31-35
    • Hippe, Z.S.1    Iwaszek, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.