Matric

REi·2024년 4월 30일
Matric

Algorithm

목록 보기
4/4

1. 정확도 (Accuracy)

(TP+TN)(TP+TN+FP+FN)\frac{(TP+TN)}{(TP+TN+FP+FN)}

2. 정밀도 (Precision)

TP(TP+FP)\frac{TP}{(TP+FP)}

3. 재현율 (Recall)

TP(TP+FN)\frac{TP}{(TP+FN)}

4. 특이도 (Specificity), 실제 부정 비율 (True Negative Rate)

TN(TN+FP)\frac{TN}{(TN+FP)}

5. F1 Score

2∗(Precision∗Recall)(Precision+Recall)\frac{2*(Precision*Recall)}{(Precision+Recall)}

6. False Positive Rate (FPR)

FP(FP+TN)\frac{FP}{(FP+TN)}

7. False Negative Rate (FNR)

FN(FN+TP)\frac{FN}{(FN+TP)}

8. Positive Predictive Value (PPV)

TP(TP+FP)\frac{TP}{(TP+FP)}

9. Negative Predictive Value (NPV)

TN(TN+FN)\frac{TN}{(TN+FN)}

10. Matthews Correlation Coefficient (MCC)

(TP∗TN−FP∗FN)((TP+FP)∗(TP+FN)∗(TN∗FP)∗(TN+FN)\frac{(TP*TN-FP*FN)}{(\sqrt{(TP+FP)*(TP+FN)*(TN*FP)*(TN+FN)}}

11. Informedness

Recall+Specificity−1Recall + Specificity -1

12. Markedness

PPV+NPV−1PPV+NPV-1
profile
REi
이전 포스트

Simple Linear Regression

0개의 댓글