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Volumn 4488 LNCS, Issue PART 2, 2007, Pages 482-485

Building behavior scoring model using genetic algorithm and support vector machines

Author keywords

Behavior scoring; Data mining; Feature selection; Genetic algorithm; Multi class support vector machines

Indexed keywords

BEHAVIORAL RESEARCH; DATA MINING; FEATURE EXTRACTION; GENETIC ALGORITHMS; SUPPORT VECTOR MACHINES;

EID: 38049179196     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-72586-2_69     Document Type: Conference Paper
Times cited : (8)

References (8)
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    • 10644295762 scopus 로고    scopus 로고
    • The contribution of data mining to information science
    • Chen, S., Liu, X: The contribution of data mining to information science. Journal of Information Science. 30(2004) 550-558
    • (2004) Journal of Information Science , vol.30 , pp. 550-558
    • Chen, S.1    Liu, X.2
  • 2
    • 0034118581 scopus 로고    scopus 로고
    • Neural network credit scoring models
    • West, D.: Neural network credit scoring models. Computers & Operations Research. 27(2000)1131-52
    • (2000) Computers & Operations Research , vol.27 , pp. 1131-1152
    • West, D.1
  • 3
    • 33746625785 scopus 로고    scopus 로고
    • Support Vector Machines Approach to Credit Assessment
    • International Conference on Computational Science, Springer-Verlag, Berlin Heidelberg New York
    • Li, J., Liu, J., Xu, W., Shi. Y.: Support Vector Machines Approach to Credit Assessment. International Conference on Computational Science. Lecture Notes in Computer Science, Vol. 3039. Springer-Verlag, Berlin Heidelberg New York (2004)
    • (2004) Lecture Notes in Computer Science , vol.3039
    • Li, J.1    Liu, J.2    Xu, W.3    Shi, Y.4
  • 4
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • Kohavi, R., John, G.H.: Wrappers for feature subset selection. Artificial Intelligence. 1(1997) 273-324
    • (1997) Artificial Intelligence , vol.1 , pp. 273-324
    • Kohavi, R.1    John, G.H.2
  • 8
    • 0031209593 scopus 로고    scopus 로고
    • Determining the saliency of input variables in neural network classifiers
    • Nath, R., Rajagopalan, B., Ryker, R.: Determining the saliency of input variables in neural network classifiers. Computers & Operations Research. 8(1997) 767-773
    • (1997) Computers & Operations Research , vol.8 , pp. 767-773
    • Nath, R.1    Rajagopalan, B.2    Ryker, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.