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Volumn 5027 LNAI, Issue , 2008, Pages 276-285

Data reduction algorithm for machine learning and data mining

Author keywords

[No Author keywords available]

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; DATA MINING; DECISION SUPPORT SYSTEMS; EDUCATION; EXPERIMENTS; FINANCIAL DATA PROCESSING; INFORMATION MANAGEMENT; INTELLIGENT CONTROL; INTELLIGENT SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MINING; POPULATION STATISTICS; ROBOT LEARNING; SEARCH ENGINES; STATISTICS; TECHNOLOGY;

EID: 48249093049     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-69052-8_29     Document Type: Conference Paper
Times cited : (17)

References (19)
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    • (2004) Pattern Recognition Letters
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  • 3
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    • An Approach to Instance Reduction in Supervised Learning
    • Coenen, F, Preece, A, Macintosh, A, eds, Springer, London
    • Czarnowski, I., Jȩdrzejowicz, P.: An Approach to Instance Reduction in Supervised Learning. In: Coenen, F., Preece, A., Macintosh, A. (eds.) Research and Development in Intelligent Systems, vol. XX, pp. 267-282. Springer, London (2004)
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    • Czarnowski, I.1    Jȩdrzejowicz, P.2
  • 4
    • 0013326060 scopus 로고    scopus 로고
    • Feature Selection for Classification
    • Dash, M., Liu, H.: Feature Selection for Classification. Intelligence Data Analysis 1(3), 131-156 (1997)
    • (1997) Intelligence Data Analysis , vol.1 , Issue.3 , pp. 131-156
    • Dash, M.1    Liu, H.2
  • 5
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    • Duch, W.: Results - Comparison of Classification. Nicolaus Copernicus University (2002), http://www.is.umk.pl/projects/datasets.html
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  • 6
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    • Glover, F.: Tabu search. Part I and II. ORSA Journal of Computing 1(3), Summer (1990) and 2(1) Winter (1990)
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  • 9
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    • Wrappers for Feature Subset Selection
    • Kohavi, R., John, G.H.: Wrappers for Feature Subset Selection. Artificial Intelligence 97(1-2), 273-324 (1997)
    • (1997) Artificial Intelligence , vol.97 , Issue.1-2 , pp. 273-324
    • Kohavi, R.1    John, G.H.2
  • 10
    • 31144448615 scopus 로고    scopus 로고
    • Using Simulated Annealing to Optimize the Feature Selection Problem in Marketing Applications
    • Meiri, R., Zahavi, J.: Using Simulated Annealing to Optimize the Feature Selection Problem in Marketing Applications. European Journal of Operational Research 17(3), 842-858 (2006)
    • (2006) European Journal of Operational Research , vol.17 , Issue.3 , pp. 842-858
    • Meiri, R.1    Zahavi, J.2
  • 11
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    • University of California, Department of Information and Computer Science, Irvine, CA
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  • 12
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    • Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, SanMa-teo
  • 14
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    • Selecting Representative Examples and Attributes by a Genetic Algorithm
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    • Talukdar, S., Baerentzen, L., Gove, A., de Souza, P.: Asynchronous Teams: Cooperation Schemes for Autonomous. Computer-Based Agents. Technical Report EDRC 18-59-96, Carnegie Mellon University, Pittsburgh (1996)
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    • Reduction Techniques for Instance-based Learning Algorithm
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    • Wilson, D.R.1    Martinez, T.R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.