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Volumn 32, Issue 7, 1999, Pages 1139-1147

Comparing classifiers when the misallocation costs are uncertain

Author keywords

Classification rule; Error rate; Loss function; Misclassification costs; Roc curve; Supervised classification

Indexed keywords

ERRORS; GRAPH THEORY; PROBABILITY; STATISTICAL METHODS; VECTORS;

EID: 0033164667     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(98)00154-X     Document Type: Article
Times cited : (142)

References (10)
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  • 7
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    • The use of the area under the ROC curve in evaluation of machine learning algorithms
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  • 8
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    • Analysis and visualisation of classifier performance: Comparison under imprecise class and cost distributions
    • D. Heckerman, H. Mannila, D.P.R. Uthurusamy (Eds.)
    • [8] F. Provost, T. Fawcett, Analysis and visualisation of classifier performance: comparison under imprecise class and cost distributions, in: D. Heckerman, H. Mannila, D.P.R. Uthurusamy (Eds.), Proc. 3rd Int. Conf. on Knowledge Discovery and Data Mining, (1997) pp. 43-48.
    • (1997) Proc. 3rd Int. Conf. on Knowledge Discovery and Data Mining , pp. 43-48
    • Provost, F.1    Fawcett, T.2
  • 9
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    • A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data
    • [9] S. Wieand, M.H. Gail, B.R. James, K.L. James. A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data, Biometrika 76 (1989) 585-592.
    • (1989) Biometrika , vol.76 , pp. 585-592
    • Wieand, S.1    Gail, M.H.2    James, B.R.3    James, K.L.4
  • 10
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    • Analyzing a portion of the ROC curve
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    • McClish, D.K.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.