Table 1.
Results of Regression Example 1. The numbers in parentheses show the corresponding standard deviations. MPE stands for mean prediction error, TP and FN represent true positive rates and false negative rates, respectively.
| p0 | Method | n = 50 | n = 100 | ||||||
|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||
| Train MPE | Test MPE | TP | FN | Train MPE | Test MPE | TP | FN | ||
| 2 | Linear Ridge | 15.89 (4.46) | 17.96 (1.33) | – | – | 16.29 (3.46) | 17.82 (1.16) | – | – |
| LASSO | 15.89 (4.47) | 17.96 (1.32) | 1 | 0.49 | 16.29 (3.46) | 17.82 (1.17) | 1 | 0.5 | |
| L2 Kernel | 2.06 (0.45) | 11.17 (2.00) | – | – | 2.09 (0.38) | 7.36 (1.55) | – | – | |
| SIS | 8.22 (5.50) | 12.20 (7.13) | 0.42 | 0.29 | 5.39 (5.85) | 7.54 (7.51) | 0.68 | 0.16 | |
| RFE | 4.77 (3.91) | 10.57 (6.05) | 0.44 | 0.30 | 3.10 (3.51) | 5.44 (5.02) | 0.7 | 0.16 | |
| COSSO | 7.05 (6.56) | 11.99 (10.32) | 0.56 | 0.39 | 0.96 (1.29) | 1.99 (2.58) | 0.98 | 0.53 | |
| KNIFE | 3.66 (0.48) | 6.14 (2.00) | 1 | 0.14 | 2.35 (0.19) | 3.03 (0.57) | 1 | 0 | |
| DOSK | 1.42 (0.21) | 3.40 (2.92) | 1 | 0.04 | 0.92 (0.13) | 1.42 (0.19) | 1 | 0 | |
|
| |||||||||
| 8 | Linear Ridge | 13.77 (2.89) | 18.09 (1.55) | – | – | 16.11 (2.78) | 17.68 (1.03) | – | – |
| LASSO | 13.77 (2.89) | 18.12 (2.15) | 1 | 0.87 | 16.13 (2.77) | 17.61 (1.02) | 1 | 0.88 | |
| L2 Kernel | 0.05 (0.01) | 17.26 (1.52) | – | – | 0.05 (0.01) | 15.76 (1.05) | – | – | |
| SIS | 3.94 (2.04) | 16.18 (4.44) | 0.46 | 0.31 | 3.07 (1.90) | 9.01 (3.95) | 0.86 | 0.26 | |
| RFE | 9.83 (4.97) | 16.18 (12.30) | 0.54 | 0.24 | 6.44 (5.73) | 10.29 (6.03) | 0.86 | 0.25 | |
| COSSO | 12.27 (40.97) | 19.93 (12.30) | 0.54 | 0.24 | 6.44 (5.73) | 10.29 (8.66) | 0.76 | 0.25 | |
| KNIFE | 2.40 (0.53) | 13.89 (3.64) | 1 | 0.42 | 1.58 (0.18) | 2.69 (1.99) | 1 | 0.22 | |
| DOSK | 2.70 (0.59) | 10.80 (5.59) | 0.95 | 0.29 | 1.12 (0.20) | 2.15 (2.81) | 1 | 0.20 | |