Classification on Dataset-3 OpenML-CC18 (test)
50.33AccuracySubTab
Evaluation results
| Method | Links | |
|---|---|---|
| SubTabArchitecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 50.33 | |
| SubTab w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 49.93 | |
| AE w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 49.43 | |
| Autoencoder (AE)Architecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 49.07 | |
| Logistic RegressionEvaluation protocol=Raw features2021.10 | 46.93 | |
| VIME-selfArchitecture=[256, 256, 256, 256], Evaluation protocol=Logistic regression on embeddings2021.10 | 46.08 |