Partial Dependence Plot (PDP) Calculation on diabetes
0.02Running Time (s)scikit-learn
Evaluation Results
| Method | Links | |
|---|---|---|
| scikit-learnTask=Approx. PDP, k=5, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.02 | |
| scikit-learnTask=Exact PDP, k=5, Model=HistGradientBoostingRegressor, Number of trees=100, Hardware=Google Colab high-RAM CPU2026.05 | 0.25 | |
| FastPDTask=Any-Order-PDIVs, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.3 | |
| WOODELF++Task=Exact PDP, k=10, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.36 | |
| WOODELF++Task=Exact PDP, k=5, Model=HistGradientBoostingRegressor, Number of trees=100, Hardware=Google Colab high-RAM CPU2026.05 | 0.39 | |
| scikit-learnTask=Exact PDP, k=10, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.4 | |
| WOODELF++Task=Exact PDP, k=100, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.4 | |
| WOODELF++Task=Approx. PDP, k=5, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.4 | |
| WOODELF++Task=Exact full PDP, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.44 | |
| WOODELF++Task=Any-Order-PDIVs, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 0.92 | |
| scikit-learnTask=Exact full PDP, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 1.26 | |
| scikit-learnTask=Exact PDP, k=100, Model=HistGradientBoostingRegressor, Number of trees=1002026.05 | 2.73 |