Sparse Regression on leukemia
0.01CPU TimeAPG+
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| APG+Sparsity level (s)=2m, Tolerance (epsilon)=10^-62022.11 | 0.01 | 12 | 42 | 0.944 | |
| APG-LL+Sparsity level (s)=2m, Tolerance (epsilon)=10^-62022.11 | 0.01 | 43 | 29 | 0.926 | |
| APG+Sparsity level (s)=m, Tolerance (epsilon)=10^-62022.11 | 0.02 | 15 | 104 | 4.722 | |
| APG-LL+Sparsity level (s)=m, Tolerance (epsilon)=10^-62022.11 | 0.02 | 118 | 104 | 4.722 | |
| APG+Sparsity level (s)=[1.1m], Tolerance (epsilon)=10^-62022.11 | 0.02 | 17 | 98 | 9.202 | |
| APG-LL+Sparsity level (s)=[1.1m], Tolerance (epsilon)=10^-62022.11 | 0.02 | 112 | 98 | 9.202 | |
| APG+Sparsity level (s)=[1.5m], Tolerance (epsilon)=10^-62022.11 | 0.02 | 19 | 53 | 1.369 | |
| APG-LL+Sparsity level (s)=[1.5m], Tolerance (epsilon)=10^-62022.11 | 0.03 | 81 | 49 | 1.23 | |
| APGSparsity level (s)=2m, Tolerance (epsilon)=10^-62022.11 | 0.47 | 574 | 0 | 0.619 | |
| APGSparsity level (s)=[1.5m], Tolerance (epsilon)=10^-62022.11 | 0.69 | 865 | 0 | 0.694 | |
| APGSparsity level (s)=m, Tolerance (epsilon)=10^-62022.11 | 1.05 | 1,202 | 0 | 0.967 | |
| APGSparsity level (s)=[1.1m], Tolerance (epsilon)=10^-62022.11 | 1.06 | 1,445 | 0 | 0.98 | |
| PG-LLSparsity level (s)=2m, Tolerance (epsilon)=10^-62022.11 | 1.38 | 2,862 | 0 | 0.714 | |
| PG-LLSparsity level (s)=[1.1m], Tolerance (epsilon)=10^-62022.11 | 1.87 | 3,968 | 0 | 1.718 | |
| PG-LLSparsity level (s)=[1.5m], Tolerance (epsilon)=10^-62022.11 | 1.92 | 3,952 | 0 | 1.074 | |
| PGSparsity level (s)=m, Tolerance (epsilon)=10^-62022.11 | 4.22 | 10,000 | 0 | 0.649 | |
| PGSparsity level (s)=[1.1m], Tolerance (epsilon)=10^-62022.11 | 4.3 | 10,000 | 0 | 0.703 | |
| PGSparsity level (s)=2m, Tolerance (epsilon)=10^-62022.11 | 4.3 | 10,000 | 0 | 0.704 | |
| PGSparsity level (s)=[1.5m], Tolerance (epsilon)=10^-62022.11 | 4.36 | 10,000 | 0 | 0.73 | |
| PG-LLSparsity level (s)=m, Tolerance (epsilon)=10^-62022.11 | 9.64 | 20,000 | 0 | 1.05 |