Table 2 Performance after outlier detection in liver cancer mass spectrometry data.
From: A kernel-based approach for detecting outliers of high-dimensional biological data
Measurements | Without outlier removal | After outlier removal | ||
|---|---|---|---|---|
| Â | Â | KLOD | Mahalanobis | One-class SVM |
Specificity (%) | 93.63 | 94.69 | 94.29 | 94.35 |
Sensitivity (%) | 92.82 | 93.95 | 93.51 | 93.89 |
Accuracy (%) | 93.14 | 94.23 | 93.82 | 94.07 |
No. of the outliers | Cirrhosis | 3 | 2 | 5 |
| Â | HCC | 2 | 4 | 6 |