Research Article
Evidence Maximization Technique for Training of Elastic Nets
Table 1
Elastic nets trained with several fixed regularization parameters
and
.
| | | Sparseness (%) | Mean log likelihood | Error (%) |
| 0 | 0 | 2.46 ± 0.00 | 0.0638 ± 0.0007 | 2.06 ± 0.05 | 3 | | 10.32 ± 1.56 | 0.0583 ± 0.0011 | 1.85 ± 0.05 | 10 | | 16.84 ± 2.49 | 0.0609 ± 0.0007 | 1.81 ± 0.06 | 30 | | 45.87 ± 4.03 | 0.0823 ± 0.0005 | 2.18 ± 0.05 | 100 | | 63.26 ± 2.90 | 0.1419 ± 0.0003 | 3.41 ± 0.05 | 300 | | 75.77 ± 4.37 | 0.2503 ± 0.0004 | 5.19 ± 0.05 |
| 1 | 1 | 3.75 ± 0.16 | 0.0621 ± 0.0007 | 2.00 ± 0.04 | 1 | 10 | 3.81 ± 0.19 | 0.0621 ± 0.0007 | 2.00 ± 0.04 | 1 | 30 | 6.71 ± 2.54 | 0.0607 ± 0.0013 | 1.95 ± 0.07 | 10 | 1 | 16.73 ± 2.40 | 0.0609 ± 0.0007 | 1.81 ± 0.06 | 10 | 10 | 16.56 ± 2.46 | 0.0613 ± 0.0007 | 1.81 ± 0.06 | 10 | 30 | 16.25 ± 2.53 | 0.0621 ± 0.0006 | 1.82 ± 0.05 | 10 | 100 | 16.20 ± 3.09 | 0.0649 ± 0.0005 | 1.86 ± 0.05 | 30 | 100 | 38.42 ± 2.42 | 0.0862 ± 0.0005 | 2.20 ± 0.05 | 100 | 30 | 61.51 ± 2.45 | 0.1428 ± 0.0003 | 3.41 ± 0.05 | 100 | 100 | 59.18 ± 2.09 | 0.1445 ± 0.0003 | 3.41 ± 0.05 |
| 0 | 1 | 2.46 ± 0.00 | 0.0638 ± 0.0007 | 2.06 ± 0.05 | | 10 | 2.46 ± 0.00 | 0.0638 ± 0.0007 | 2.06 ± 0.04 | | 100 | 2.46 ± 0.00 | 0.0638 ± 0.0007 | 2.05 ± 0.04 | | 300 | 2.46 ± 0.00 | 0.0659 ± 0.0006 | 2.05 ± 0.06 |
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