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- 학술저널
- 한국데이터정보과학회
- 한국데이터정보과학회지
- 한국데이터정보과학회지 제32권 제2호
- 2021.03
- 427 - 437 (11 pages)
- KCI우수등재
DOI : 10.7465/jkdi.2021.32.2.427
초록
There is a well known 2 by 2 confusion matrix which is widely used in biostatistics or credit assessment. Using these, not only the true positive rate (TPR) and true negative rate (TNR) but also the positive predictive value (PPV) and negative predictive value (NPV) statistics are obtained. In this study, we propose the confusion plot which is a graphical method can geometrically describe various statistics defined from the confusion matrix. The confusion plot consists of six right-angled triangles using equations expressed as the sum of rows and columns of the confusion matrix. In particular, it is found that TPR, TNR, PPV and NPV can be described as acute angles of right-angled triangles in the confusion plot. This confusion plot can evaluate the classification model and its performance similarly to the well known ROC curve. Therefore, the confusion plot could be useful in evaluating the classification models similar to the ROC curve.
목차
Abstract
1. Introduction
2. TPR - TNR plot and PPV - NPV plot
3. Confusion plot
4. Illustrative examples
5. Confusion matrices obtained from various normal distributions
6. Empirical data example
7. Conclusions
References
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