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Volumn 13, Issue , 2012, Pages 2813-2869

A unified view of performance metrics: Translating threshold choice into expected classification loss

Author keywords

Area under the ROC curve (AUC); Brier score; Calibration loss; Classification performance metrics; Cost sensitive evaluation; Operating condition; Refinement loss

Indexed keywords

AREA UNDER THE ROC CURVE; BRIER SCORE; CLASSIFICATION PERFORMANCE; COST-SENSITIVE EVALUATION; OPERATING CONDITION;

EID: 84869160181     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (206)

References (59)
  • 1
    • 0033164667 scopus 로고    scopus 로고
    • Comparing classifiers when the misallocation costs are uncertain
    • N. M. Adams and D. J. Hand. Comparing classifiers when the misallocation costs are uncertain. Pattern Recognition, 32(7):1139-1147, 1999.
    • (1999) Pattern Recognition , vol.32 , Issue.7 , pp. 1139-1147
    • Adams, N.M.1    Hand, D.J.2
  • 2
    • 0142026284 scopus 로고    scopus 로고
    • Estimating disease prevalence in two-phase studies
    • T. A. Alonzo, M. S. Pepe, and T. Lumley. Estimating disease prevalence in two-phase studies. Biostatistics, 4(2):313-326, 2003.
    • (2003) Biostatistics , vol.4 , Issue.2 , pp. 313-326
    • Alonzo, T.A.1    Pepe, M.S.2    Lumley, T.3
  • 6
    • 0003010182 scopus 로고
    • Verification of forecasts expressed in terms of probability
    • G. W. Brier. Verification of forecasts expressed in terms of probability. Monthly Weather Review, 78(1):1-3, 1950.
    • (1950) Monthly Weather Review , vol.78 , Issue.1 , pp. 1-3
    • Brier, G.W.1
  • 10
    • 0034592774 scopus 로고    scopus 로고
    • Explicitly representing expected cost: An alternative to roc representation
    • C. Drummond and R. C. Holte. Explicitly representing expected cost: an alternative to ROC representation. In Knowledge Discovery and Data Mining, pages 198-207, 2000.
    • (2000) Knowledge Discovery and Data Mining , pp. 198-207
    • Drummond, C.1    Holte, R.C.2
  • 11
    • 33748991193 scopus 로고    scopus 로고
    • Cost curves: An improved method for visualizing classifier performance
    • DOI 10.1007/s10994-006-8199-5
    • C. Drummond and R. C. Holte. Cost curves: an improved method for visualizing classifier performance. Machine Learning, 65(1):95-130, 2006. (Pubitemid 44451195)
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 95-130
    • Drummond, C.1    Holte, R.C.2
  • 14
    • 33646023117 scopus 로고    scopus 로고
    • An introduction to roc analysis
    • T. Fawcett. An introduction to ROC analysis. Pattern Recognition Letters, 27(8):861-874, 2006.
    • (2006) Pattern Recognition Letters , vol.27 , Issue.8 , pp. 861-874
    • Fawcett, T.1
  • 15
    • 34249731390 scopus 로고    scopus 로고
    • PAV and the ROC convex hull
    • DOI 10.1007/s10994-007-5011-0
    • T. Fawcett and A. Niculescu-Mizil. PAV and the ROC convex hull. Machine Learning, 68(1): 97-106, July 2007. (Pubitemid 46828728)
    • (2007) Machine Learning , vol.68 , Issue.1 , pp. 97-106
    • Fawcett, T.1    Niculescu-Mizil, A.2
  • 18
    • 70349280929 scopus 로고    scopus 로고
    • An experimental comparison of performance measures for classification
    • ISSN 0167-8655
    • C. Ferri, J. Herńandez-Orallo, and R. Modroiu. An experimental comparison of performance measures for classification. Pattern Recognition Letters, 30(1):27-38, 2009. ISSN 0167-8655.
    • (2009) Pattern Recognition Letters , vol.30 , Issue.1 , pp. 27-38
    • Ferri, C.1    Herńandez-Orallo, J.2    Modroiu, R.3
  • 23
    • 50549093309 scopus 로고    scopus 로고
    • Quantifying counts and costs via classification
    • G. Forman. Quantifying counts and costs via classification. DataMining and Knowledge Discovery, 17(2):164-206, 2008.
    • (2008) DataMining and Knowledge Discovery , vol.17 , Issue.2 , pp. 164-206
    • Forman, G.1
  • 24
    • 21744462998 scopus 로고    scopus 로고
    • On bias, variance, 0/1loss, and the curse-of-dimensionality
    • J. H. Friedman. On bias, variance, 0/1loss, and the curse-of- dimensionality. Data Mining and Knowledge Discovery, 1(1):55-77, 1997.
    • (1997) Data Mining and Knowledge Discovery , vol.1 , Issue.1 , pp. 55-77
    • Friedman, J.H.1
  • 26
    • 33947274775 scopus 로고    scopus 로고
    • Strictly proper scoring rules, prediction, and estimation
    • ISSN 0162-1459
    • T. Gneiting and A.E. Raftery. Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association, 102(477):359-378, 2007. ISSN 0162-1459.
    • (2007) Journal of the American Statistical Association , vol.102 , Issue.477 , pp. 359-378
    • Gneiting, T.1    Raftery, A.E.2
  • 29
    • 69549133517 scopus 로고    scopus 로고
    • Measuring classifier performance: A coherent alternative to the area under the roc curve
    • D. J. Hand. Measuring classifier performance: a coherent alternative to the area under the ROC curve. Machine Learning, 77(1):103-123, 2009.
    • (2009) Machine Learning , vol.77 , Issue.1 , pp. 103-123
    • Hand, D.J.1
  • 30
    • 77953705269 scopus 로고    scopus 로고
    • Evaluating diagnostic tests: The area under the roc curve and the balance of errors
    • D. J. Hand. Evaluating diagnostic tests: the area under the ROC curve and the balance of errors. Statistics in Medicine, 29(14):1502-1510, 2010.
    • (2010) Statistics in Medicine , vol.29 , Issue.14 , pp. 1502-1510
    • Hand, D.J.1
  • 35
    • 1942452386 scopus 로고    scopus 로고
    • Improving accuracy and cost of two-class and multi-class probabilistic classifiers using roc curves
    • N. Lachiche and P. Flach. Improving accuracy and cost of two-class and multi-class probabilistic classifiers using roc curves. In International Conference on Machine Learning, pages 416-423, 2003.
    • (2003) International Conference on Machine Learning , pp. 416-423
    • Lachiche, N.1    Flach, P.2
  • 38
    • 0000774379 scopus 로고
    • A note on the utility of probabilistic predictions and the probability score in the cost-loss ratio decision situation
    • ISSN 0894-8763
    • A. H. Murphy. A note on the utility of probabilistic predictions and the probability score in the cost-loss ratio decision situation. Journal of Applied Meteorology, 5:534-536, 1966. ISSN 0894-8763.
    • (1966) Journal of Applied Meteorology , vol.5 , pp. 534-536
    • Murphy, A.H.1
  • 39
    • 0347279633 scopus 로고
    • Measures of the utility of probabilistic predictions in cost-loss ratio decision situations in which knowledge of the cost-loss ratios is incomplete
    • ISSN 0894-8763
    • A. H. Murphy. Measures of the utility of probabilistic predictions in cost-loss ratio decision situations in which knowledge of the cost-loss ratios is incomplete. Journal of Applied Meteorology, 8:863-873, 1969. ISSN 0894-8763.
    • (1969) Journal of Applied Meteorology , vol.8 , pp. 863-873
    • Murphy, A.H.1
  • 40
    • 0000918735 scopus 로고
    • A new vector partition of the probability score
    • A. H. Murphy. A new vector partition of the probability score. Journal of Applied Meteorology, 12: 595-600, 1973.
    • (1973) Journal of Applied Meteorology , vol.12 , pp. 595-600
    • Murphy, A.H.1
  • 41
    • 0000477291 scopus 로고
    • Scoring rules in probability assessment and evaluation
    • A. H. Murphy and R. L. Winkler. Scoring rules in probability assessment and evaluation. Acta Psychologica, 34:273-286, 1970.
    • (1970) Acta Psychologica , vol.34 , pp. 273-286
    • Murphy, A.H.1    Winkler, R.L.2
  • 43
    • 84946649293 scopus 로고
    • Contribution to the theory of sampling human populations
    • J. Neyman. Contribution to the theory of sampling human populations. Journal of the American Statistical Association, 33(201):101-116, 1938.
    • (1938) Journal of the American Statistical Association , vol.33 , Issue.201 , pp. 101-116
    • Neyman, J.1
  • 47
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    • MIT Press, Boston
    • J. C. Platt. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In Advances in Large Margin Classifiers, pages 61-74. MIT Press, Boston, 1999.
    • (1999) Advances in Large Margin Classifiers , pp. 61-74
    • Platt, J.C.1
  • 49
    • 0035283313 scopus 로고    scopus 로고
    • Robust classification for imprecise environments
    • DOI 10.1023/A:1007601015854
    • F. Provost and T. Fawcett. Robust classification for imprecise environments. Machine Learning, 42 (3):203-231, 2001. (Pubitemid 32188799)
    • (2001) Machine Learning , vol.42 , Issue.3 , pp. 203-231
    • Provost, F.1    Fawcett, T.2
  • 54
    • 0034294901 scopus 로고    scopus 로고
    • Better decisions through science
    • October
    • J. A. Swets, R. M. Dawes, and J. Monahan. Better decisions through science. Scientific American, 283(4):82-87, October 2000.
    • (2000) Scientific American , vol.283 , Issue.4 , pp. 82-87
    • Swets, J.A.1    Dawes, R.M.2    Monahan, J.3
  • 55
    • 84950649045 scopus 로고
    • A double sampling scheme for estimating from binomial data with misclassifications
    • A. Tenenbein. A double sampling scheme for estimating from binomial data with misclassifications. Journal of the American Statistical Association, pages 1350-1361, 1970.
    • (1970) Journal of the American Statistical Association , pp. 1350-1361
    • Tenenbein, A.1
  • 57
    • 0011106352 scopus 로고
    • A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data
    • S. Wieand, M.H. Gail, B.R. James, and K.L. James. A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data. Biometrika, 76(3):585-592, 1989.
    • (1989) Biometrika , vol.76 , Issue.3 , pp. 585-592
    • Wieand, S.1    Gail, M.H.2    James, B.R.3    James, K.L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.