Regression on 1KC (R-Squared)
0.9362R-SquaredBatch Regression
Evaluation results
| Method | Links | |
|---|---|---|
| Batch RegressionAlgorithm=Pseudo-Inverse2025.12 | 0.9362 | |
| SGDLearning rate (eta)=0.01, Epochs (E)=N * 32025.12 | 0.9293 | |
| MBGDLearning rate (eta)=0.01, Mini-batch size (K)=M * 5, Epochs (E)=NK * 402025.12 | 0.912 | |
| OLR-WABase weight (Wbase)=0.5, Weight increment (Winc)=0.5, BK=N * 0.1, Mini-batch size (K)=M * 52025.12 | 0.9077 | |
| OLRLearning rate (eta)=0.01, Epochs (E)=N * 3, Regularization parameter (lambda)=0.0012025.12 | 0.9032 | |
| ORRLearning rate (eta)=0.01, Epochs (E)=N * 3, Regularization parameter (lambda)=0.0012025.12 | 0.9029 | |
| RLSRegularization parameter (lambda)=0.99, Delta (delta)=0.012025.12 | 0.855 | |
| PAVariant=PA-III, Cost parameter (C)=0.01, Sensitivity parameter (epsilon)=0.012025.12 | 0.7857 | |
| LMSLearning rate (eta)=0.0012025.12 | 0.6077 |