Average Shift Effect Estimation (δ=0.1) on Replicated Synthetic Data (Median)
0.0113Absolute BiasKDE
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| KDELearner=Kernel Density Estimation2025.10 | 0.0113 | 0.0596 | 0.0782 | |
| MLP-LSModel=Multi-Layer Perceptron, Divergence=Least Squares2025.10 | 0.013 | 0.0383 | 0.0488 | |
| MLP-NBModel=Multi-Layer Perceptron, Divergence=Negative-Binomial2025.10 | 0.0135 | 0.0376 | 0.048 | |
| MLP-KLModel=Multi-Layer Perceptron, Divergence=Kullback-Leibler2025.10 | 0.0146 | 0.0379 | 0.048 | |
| MLP-ISModel=Multi-Layer Perceptron, Divergence=Itakura-Saito2025.10 | 0.0151 | 0.0381 | 0.0483 | |
| GBM-LSModel=Gradient Boosting Machine, Divergence=Least Squares2025.10 | 0.0619 | 0.0766 | 0.0969 | |
| GBM-NBModel=Gradient Boosting Machine, Divergence=Negative-Binomial2025.10 | 0.0826 | 0.0772 | 0.0978 | |
| GBM-KLModel=Gradient Boosting Machine, Divergence=Kullback-Leibler2025.10 | 0.0845 | 0.0778 | 0.0985 | |
| KLIEPLearner=KLIEP2025.10 | 0.091 | 0.0738 | 0.0933 | |
| GBM-ISModel=Gradient Boosting Machine, Divergence=Itakura-Saito2025.10 | 0.0933 | 0.0773 | 0.0978 | |
| uLSIFLearner=uLSIF2025.10 | 0.0955 | 0.0798 | 0.0997 |