Label Noise Identification on MNIST (train)
0.998AUCacci
Evaluation Results
| Method | Links | |
|---|---|---|
| acciScoring Metric=First-Split Cumulative Accuracy2022.10 | 0.998 | |
| accfScoring Metric=Second-Split Cumulative Accuracy2022.10 | 0.998 | |
| JointScoring Metric=Combined learning and forgetting ranks2022.10 | 0.998 | |
| ssftScoring Metric=Second-Split Forgetting Time2022.10 | 0.997 | |
| fsltScoring Metric=First-Split Learning Time2022.10 | 0.973 | |
| confiScoring Metric=Confidence2022.10 | 0.965 | |
| TMC-ShapleyClassifier=Logistic Regression2022.11 | 0.933 | |
| CS-SHAPLEYClassifier=Logistic Regression2022.11 | 0.877 | |
| Beta ShapleyClassifier=Logistic Regression2022.11 | 0.845 | |
| TMC-ShapleyClassifier=SVM-RBF2022.11 | 0.747 | |
| CS-SHAPLEYClassifier=SVM-RBF2022.11 | 0.674 | |
| Beta ShapleyClassifier=SVM-RBF2022.11 | 0.51 | |
| nfScoring Metric=Number of Forgetting Events2022.10 | 0.377 | |
| Leave-One-OutClassifier=Logistic Regression2022.11 | 0.371 | |
| Leave-One-OutClassifier=SVM-RBF2022.11 | 0.254 |