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    비용곡선과 ROC곡선에서의 비용비율 = Cost Ratios for Cost and ROC Curves

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    https://www.riss.kr/link?id=A105203779

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    For classification problems on mixture distribution, a threshold based on cost functions is optimal from the viewpoint of a minimum expected cost. Assuming that there is no cost information, we propose cost ratios in the expected cost corresponding to thresholds where the total accuracy and the true rate are maximized to explain the relation of these cost ratios minimizing the expected cost. Other cost ratios are also proposed by comparing the normalized expected costs when classification accuracy is maximized. The values of these cost ratios are located between two cost ratios for the expected costs based on classification accuracies, and converge to that of the minimum expected cost. This work suggests two cost ratios: one is minimized by the expected cost and the normalized expected cost, and the other in the expected cost and the normalized expected cost functions that are maximized classification accuracies. We discuss their compatibility based on the relation of these cost ratios.
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    For classification problems on mixture distribution, a threshold based on cost functions is optimal from the viewpoint of a minimum expected cost. Assuming that there is no cost information, we propose cost ratios in the expected cost corresponding to...

    For classification problems on mixture distribution, a threshold based on cost functions is optimal from the viewpoint of a minimum expected cost. Assuming that there is no cost information, we propose cost ratios in the expected cost corresponding to thresholds where the total accuracy and the true rate are maximized to explain the relation of these cost ratios minimizing the expected cost. Other cost ratios are also proposed by comparing the normalized expected costs when classification accuracy is maximized. The values of these cost ratios are located between two cost ratios for the expected costs based on classification accuracies, and converge to that of the minimum expected cost. This work suggests two cost ratios: one is minimized by the expected cost and the normalized expected cost, and the other in the expected cost and the normalized expected cost functions that are maximized classification accuracies. We discuss their compatibility based on the relation of these cost ratios.

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    참고문헌 (Reference)

    1 홍종선, "혼합분포에서 최적분류점" 한국통계학회 23 (23): 13-28, 2010

    2 Tasche, D., "Validation of Internal Rating Systems and PD Estimates"

    3 Briggs, W. M., "The skill plot: a graphical technique for the evaluating the predictive usefulness of continuous diagnostic tests" 63 : 250-261, 2007

    4 Davis, J., "The relationship between precision-recall and ROC curves" 233-240, 2006

    5 Liu, Y., "The evaluation of classification models for credit scoring" 2 : 1-65, 2002

    6 Pepe, M. S., "The Statistical Evaluation of Medical Tests for Classification and Prediction" University Press 2003

    7 Zhou, X. H., "Statistical Methods in Diagnostic Medicine" Wiley 2002

    8 Hilden, J., "Regret graphs, diagnostic uncertainty and Youden’s index" 15 : 969-986, 1996

    9 Zweig, M. H., "Receiver-operating characteristic(ROC) plots: A fundamental evaluation tool in clinical medicine" 39 : 561-577, 1993

    10 홍종선, "ROC와 CAP 곡선에서의 최적 분류점" 한국통계학회 22 (22): 911-921, 2009

    1 홍종선, "혼합분포에서 최적분류점" 한국통계학회 23 (23): 13-28, 2010

    2 Tasche, D., "Validation of Internal Rating Systems and PD Estimates"

    3 Briggs, W. M., "The skill plot: a graphical technique for the evaluating the predictive usefulness of continuous diagnostic tests" 63 : 250-261, 2007

    4 Davis, J., "The relationship between precision-recall and ROC curves" 233-240, 2006

    5 Liu, Y., "The evaluation of classification models for credit scoring" 2 : 1-65, 2002

    6 Pepe, M. S., "The Statistical Evaluation of Medical Tests for Classification and Prediction" University Press 2003

    7 Zhou, X. H., "Statistical Methods in Diagnostic Medicine" Wiley 2002

    8 Hilden, J., "Regret graphs, diagnostic uncertainty and Youden’s index" 15 : 969-986, 1996

    9 Zweig, M. H., "Receiver-operating characteristic(ROC) plots: A fundamental evaluation tool in clinical medicine" 39 : 561-577, 1993

    10 홍종선, "ROC와 CAP 곡선에서의 최적 분류점" 한국통계학회 22 (22): 911-921, 2009

    11 Fawcett, T., "ROC graphs with instance-varying costs" 27 : 882-891, 2006

    12 Vuk, M., "ROC curve, lift chart and calibration plot" 3 : 89-108, 2006

    13 김지현, "ROC and Cost Graphs for General Cost Matrix Where Correct Classifications Incur Non-zero Costs" 한국통계학회 11 (11): 21-30, 2004

    14 Krzanowski, W. J., "ROC Curves for Continuous Data" Champman & Hall/CRC 2009

    15 Hand, D. J., "Mismatched models, wrong results, and dreadful decisions: on choosing appropriate data mining tools" 2009

    16 Jund, J., "Methods to estimate the optimal threshold for normally or log-narmally distributed biological tests" 25 : 406-415, 2005

    17 Servigny, A. D., "Measuring and Managing Credit Risk" McGraw-Hill 2004

    18 Kaivanto, K., "Maximization of the sum of sensitivity and specificity as a diagnostic cutpoint criterion" 61 : 516-518, 2008

    19 Antonie, M. L., "Learning to use a learned model: A two-stage approach to classication" 33-42, 2006

    20 Hand, D. J., "Evaluating models for classifying customers in retail banking collections" 2009

    21 Holte, R. C., "Cost-sensitive classifier evaluation using cost curves" 5012 : 26-29, 2008

    22 Turney, P. D., "Cost-sensitive classification: Empirical evaluation of a hybrid genetic decision tree induction algorithm" 2 : 369-409, 1995

    23 Drummond, C., "Cost curves: an improved method for visualizing classifier performance" 65 : 95-130, 2006

    24 Liu, Y., "Comparing evaluation metrics for sentence boundary detection" 185-188, 2007

    25 Adams, N. M., "Comparing classifiers when the misallocation costs are uncertain" 30 : 1139-1147, 1999

    26 Metz, C. E., "Basic principles of ROC analysis" 8 : 283-298, 1978

    27 Hoshino, R., "Applications and extensions of cost curves to marine container inspection" 2009

    28 Provost, F., "Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions" 43-48, 1997

    29 Fielding, A. H., "A review of methods for the measurement of prediction errors in conservation presence/absence models" 24 : 38-49, 1997

    30 Cantor, S. B., "A comparison of C/B ratios from studies using receiver operating characteristic curve analysis" 52 : 885-892, 1999

    31 Velez, D. R., "A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction" 31 : 306-315, 2007

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2022 평가 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
    2021-12-01 등재 등재후보 탈락 (해외등재 학술지 평가)
    2020-12-01 등재 등재후보로 하락 (해외등재 학술지 평가) KCI등재후보
    2015-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2012-12-21 학술지명변경 한글명 : 한국통계학회 논문집 -> Communications for Statistical Applications and Methods
    외국어명 : Communications of The Korean Statistical Society -> Communications for Statistical Applications and Methods
    KCI등재
    2011-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2009-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2008-02-05 학술지명변경 외국어명 : The Korean Communications in Statistics -> Communications of The Korean Statistical Society KCI등재
    2007-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2005-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2002-07-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2000-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.19 0.19 0.17
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.14 0.15 0.392 0.07
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