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Volumn 28, Issue 5, 2007, Pages 563-571

Feature selection algorithm for mixed data with both nominal and continuous features

Author keywords

Continuous feature; Feature selection; Mixed data; Nominal feature

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; DATA REDUCTION; IMAGE ANALYSIS;

EID: 33846088965     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2006.10.008     Document Type: Article
Times cited : (34)

References (13)
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    • (1995) J. Multivariate Anal. , vol.53 , pp. 332-342
    • Bar-Hen, A.1    Daudin, J.J.2
  • 3
    • 0031269184 scopus 로고    scopus 로고
    • On the optimality of the simple bayesian classifier under zero-one loss
    • Domingos P., and Pazzani M. On the optimality of the simple bayesian classifier under zero-one loss. Machine Learn. 29 (1997) 103-130
    • (1997) Machine Learn. , vol.29 , pp. 103-130
    • Domingos, P.1    Pazzani, M.2
  • 5
    • 33846078852 scopus 로고    scopus 로고
    • Hall, M.A., 1999. Correlation-based Feature Selection for Machine Learning. A Dissertation submit to Department of Computer Science. University of Waikato, Hamilton, NewZealand.
  • 9
    • 33846108856 scopus 로고    scopus 로고
    • Murphy, P.M., Aha, D.W., 1995. UCI Repository of Machine Learning Databases. .
  • 10
    • 33846105047 scopus 로고    scopus 로고
    • NIPS, 2001. Workshop on Variable and Feature Selection. .
  • 11
    • 0034818556 scopus 로고    scopus 로고
    • Pavlidis, P., Weston, J., Cai, J., Grundy, W.N., 2001. Gene functional classification from heterogeneous data. In: Proceedings of the Fifth Annual International Conference on Computational Biology, pp. 249-255.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.