Regression on DS1
0.9764R-SquaredBatch Regression
Evaluation results
| Method | Links | |
|---|---|---|
| Batch RegressionAlgorithm=Pseudo-Inverse2025.12 | 0.9764 | |
| RLSRegularization parameter (lambda)=0.99, Delta (delta)=0.012025.12 | 0.9762 | |
| LMSLearning rate (eta)=0.012025.12 | 0.9762 | |
| MBGDLearning rate (eta)=0.01, Mini-batch size (K)=M * 5, Epochs (E)=NK * 52025.12 | 0.9758 | |
| OLRLearning rate (eta)=0.01, Epochs (E)=N * 2, Regularization parameter (lambda)=0.12025.12 | 0.9757 | |
| SGDLearning rate (eta)=0.01, Epochs (E)=N * 22025.12 | 0.9756 | |
| OLR-WABase weight (Wbase)=0.5, Weight increment (Winc)=0.5, BK=N * 0.1, Mini-batch size (K)=M * 52025.12 | 0.9742 | |
| PAVariant=PA-III, Cost parameter (C)=0.1, Sensitivity parameter (epsilon)=0.12025.12 | 0.9738 | |
| ORRLearning rate (eta)=0.01, Epochs (E)=N * 2, Regularization parameter (lambda)=0.12025.12 | 0.9676 |