Regression on MCPD
0.7432R-SquaredBatch Regression
Evaluation results
| Method | Links | |
|---|---|---|
| Batch RegressionAlgorithm=Pseudo-Inverse2025.12 | 0.7432 | |
| OLRLearning rate (eta)=0.001, Epochs (E)=N * 2, Regularization parameter (lambda)=0.012025.12 | 0.7422 | |
| OLR-WABase weight (Wbase)=0.5, Weight increment (Winc)=0.5, BK=N * 0.1, Mini-batch size (K)=M * 52025.12 | 0.7408 | |
| ORRLearning rate (eta)=0.001, Epochs (E)=N * 2, Regularization parameter (lambda)=0.0012025.12 | 0.7407 | |
| RLSRegularization parameter (lambda)=0.99, Delta (delta)=0.012025.12 | 0.7383 | |
| LMSLearning rate (eta)=0.012025.12 | 0.7364 | |
| SGDLearning rate (eta)=0.01, Epochs (E)=N * 22025.12 | 0.7309 | |
| MBGDLearning rate (eta)=0.01, Mini-batch size (K)=M * 5, Epochs (E)=NK * 102025.12 | 0.7301 | |
| PAVariant=PA-III, Cost parameter (C)=0.01, Sensitivity parameter (epsilon)=0.012025.12 | 0.7289 |