Table 6. Fitting Process for Hyperparameters.
iteration | fun value | norm grad | norm step | curv | gamma | alpha | accept |
---|---|---|---|---|---|---|---|
0 | 4.06 × 104 | 5.15 × 104 | 0.00 × 100 | 1.94 × 10–5 | 0.00 × 100 | yes | |
1 | 9.33 × 103 | 7.59 × 103 | 1.19 × 100 | ok | 2.23 × 10–5 | 1.00 × 100 | yes |
2 | 8.02 × 103 | 5.57 × 103 | 1.86 × 10–1 | ok | 8.29 × 10–5 | 1.00 × 100 | yes |
3 | 6.00 × 103 | 2.30 × 103 | 5.10 × 10–1 | ok | 1.41 × 10–4 | 1.00 × 100 | yes |
4 | 5.38 × 103 | 1.13 × 103 | 3.59 × 10–1 | ok | 2.80 × 10–4 | 1.00 × 100 | yes |
5 | 5.08 × 103 | 4.84 × 102 | 3.71 × 10–1 | ok | 5.02 × 10–4 | 1.00 × 100 | yes |
6 | 4.91 × 103 | 2.41 × 102 | 4.08 × 10–1 | ok | 1.39 × 10–3 | 1.00 × 100 | yes |
7 | 4.80 × 103 | 1.46 × 102 | 5.36 × 10–1 | ok | 2.85 × 10–3 | 1.00 × 100 | yes |
8 | 4.75 × 103 | 6.98 × 101 | 5.79 × 10–1 | ok | 2.75 × 10–3 | 1.00 × 100 | yes |
9 | 4.73 × 103 | 1.01 × 102 | 4.79 × 10–1 | ok | 1.43 × 10–3 | 1.00 × 100 | yes |
10 | 4.73 × 103 | 3.80 × 101 | 1.07 × 10–1 | ok | 6.62 × 10–4 | 1.00 × 100 | yes |