Table 8.
Average and std of data utility metrics computed on the BREAST large-set
| PCD ↓ | Log-Cluster ↓ | CrCl-RS (1) | CrCl-SR (1) | Supp. Coverage ↑ | |
|---|---|---|---|---|---|
| Method | |||||
| IM | 8.94 (0.01) | -3.56 (0.12) | 0.7 (0.0) | 1.0 (0.0) | 0.99 (0.0) |
| BN | 4.88 (0.02) | -4.51 (0.38) | 0.94 (0.0) | 1.0 (0.0) | 0.99 (0.0) |
| MPoM | 2.3 (0.01) | -7.83 (0.38) | 0.85 (0.0) | 1.01 (0.0) | 0.99 (0.0) |
| CLGP | 0.69 (0.02) | -8.2 (0.27) | 0.95 (0.0) | 1.02 (0.0) | 1.0 (0.0) |
| MC-MedGAN | – (–) | -1.39 (0.0) | 0.76 (0.05) | 0.58 (0.0) | 0.16 (0.0) |
| MICE-LR | 1.31 (0.04) | -5.77 (0.13) | 0.87 (0.0) | 1.07 (0.01) | 0.99 (0.0) |
| MICE-LR-DESC | 2.94 (0.07) | -5.09 (0.14) | 0.85 (0.0) | 1.04 (0.0) | 1.0 (0.0) |
| MICE-DT | 0.14 (0.02) | -11.14 (0.53) | 1.01 (0.0) | 1.0 (0.0) | 0.99 (0.0) |
CLGP presented the overall best performance. It was not possible to compute PCD metric for MC-MedGAN as the method generated at least one variable with a unique value. The symbols on the right side of metric’s name indicate: ↑ the higher the better, ↓ the lower the better, and (1) the closer to one the better