Off-Policy Evaluation on Digits (UCI)
0.0006MSEMR
Evaluation results
| Method | Links | |
|---|---|---|
| MRnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0006 | |
| MRnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0034 | |
| DRosnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0384 | |
| DRnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0464 | |
| DMnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0485 | |
| SwitchDRnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0557 | |
| IPWnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0844 | |
| DRosnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0847 | |
| SwitchDRnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.0982 | |
| DRnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.1334 | |
| DMnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.1508 | |
| IPWnumber of evaluation data (n)=1000, number of training data (m)=500, alpha* (target policy parameter)=0.62023.12 | 0.1632 |