Symbolic Regression on Newton-Liepnik rho = 2% (test)
0.996R^2 (x_dot)GESR
Evaluation Results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| GESRd=3, noise level (rho)=2%2026.05 | 0.996 | 0.996 | 0.995 | 0.994 | 0.885 | |
| GESRd=4, noise level (rho)=2%2026.05 | 0.995 | 0.995 | 0.994 | 0.996 | 0.841 | |
| PySRd=3, noise level (rho)=2%2026.05 | 0.994 | 0.993 | 0.993 | 0.993 | 0.845 | |
| SNIPd=3, noise level (rho)=2%2026.05 | 0.992 | 0.991 | 0.991 | 0.991 | 0.761 | |
| PySRd=4, noise level (rho)=2%2026.05 | 0.992 | 0.993 | 0.993 | 0.993 | 0.783 | |
| NGGPd=3, noise level (rho)=2%2026.05 | 0.991 | 0.99 | 0.989 | 0.99 | 0.742 | |
| SNIPd=4, noise level (rho)=2%2026.05 | 0.99 | 0.991 | 0.99 | 0.99 | 0.711 | |
| NGGPd=4, noise level (rho)=2%2026.05 | 0.989 | 0.99 | 0.989 | 0.989 | 0.694 | |
| GPlearnd=3, noise level (rho)=2%2026.05 | 0.988 | 0.987 | 0.986 | 0.987 | 0.593 | |
| GPlearnd=4, noise level (rho)=2%2026.05 | 0.986 | 0.987 | 0.985 | 0.986 | 0.541 |