[논문]오즈 곡선과 최적분류점

홍종선; 오태규; 오세현

doi:10.5351/kjas.2021.34.5.807

오즈 곡선과 최적분류점
Odds curve and optimal threshold 원문보기

응용통계연구 = The Korean journal of applied statistics, v.34 no.5, 2021년, pp.807 - 822

홍종선 (성균관대학교 통계학과) , 오태규 (성균관대학교 통계학과) , 오세현 (성균관대학교 통계학과)

초록
AI-Helper

오즈 곡선으로 설명이 가능한 정확도 측도들을 살펴보고, 오즈 곡선의 성질을 바탕으로 대안적인 최대 사각형 정확도 측도를 제안한다. 다양한 확률분포함수와 실증예제를 고려하여 정확도 측도들에 대응하는 분류점을 구하고, 분류점을 측정하는 통계량들을 비교하면서 특징을 토론한다. 그러므로 ROC 곡선 등과 유사하게 오즈 곡선으로부터도 최적분류점들을 발견하고 설명할 수 있으며, 최대사각형 측도는 이진 분류모형의 성능을 향상시킬 수 있는 정확도 측도로 활용할 수 있다.

Abstract ▼ AI-Helper

Various accuracy measures that can be explained on the odds curve are discussed, and an alternative accuracy measure, the maximum square, is proposed based on the characteristics of the odds curve. Thresholds corresponding to these accuracy measures are obtained by considering various probability distribution functions and an illustrative example. Their characteristics are discussed while comparing many kinds of statistics measuring thresholds. Therefore, we can conclude that optimal thresholds could be explored from the odds curve, similar to the ROC curve, and that the maximum square measure can be used as a good accuracy measure that can improve the performance of the binary classification model.

주제어

표/그림 (14)

그림 Figure 1: Threshold on odds curve.
그림 Figure 2: MR on odds curve.
그림 Figure 3: Thresholds on Odds curve when σ²_d = σ²_n.
표 Table 1: Thresholds when σ²_d = σ²_n
그림 Figure 4: Thresholds on Odds curve when σ²_d ≠ σ²_n.
표 Table 2: Various measures
표 Table 3: Thresholds when σ²_d > σ²_n
표 Table 4: Various measures
표 Table 5: Thresholds when σ²_d < σ²_n
표 Table 6: Various measures
그림 Figure 5: Two cdf's and an odds curve.
표 Table 7: RS rating data of K bank
표 Table 8: Thresholds and confusion matrices
표 Table 9: Various measures

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