Classification on Dataset-2 OpenML-CC18 (test)
89.81AccuracySubTab w/ Dropout
Evaluation results
| Method | Links | |
|---|---|---|
| SubTab w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 89.81 | |
| SubTabArchitecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 89.37 | |
| AE w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 86.87 | |
| Autoencoder (AE)Architecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 86.83 | |
| Logistic RegressionEvaluation protocol=Raw features2021.10 | 86.46 | |
| VIME-selfArchitecture=[256, 256, 256, 256], Evaluation protocol=Logistic regression on embeddings2021.10 | 74.23 |