Table 3 Summary statistics for detecting good and bad objects in datasets 7-10 from SCOD algorithm
From: Thresher: determining the number of clusters while removing outliers
Scenarios and datasets | 96 variables, 24 objects | 24 variables, 96 objects | ||||||
|---|---|---|---|---|---|---|---|---|
Dataset 7 | Dataset 8 | Dataset 9 | Dataset 10 | Dataset 7 | Dataset 8 | Dataset 9 | Dataset 10 | |
Sensitivity | 0.337 | 0.344 | 0.327 | 0.328 | 0.225 | 0.228 | 0.223 | 0.217 |
Specificity | 0.670 | 0.661 | 0.674 | 0.658 | 0.780 | 0.774 | 0.780 | 0.786 |
FDR | 0.660 | 0.663 | 0.333 | 0.342 | 0.661 | 0.666 | 0.333 | 0.338 |
AUC | 0.504 | 0.502 | 0.501 | 0.493 | 0.502 | 0.501 | 0.502 | 0.501 |