Classification on Dataset-5 OpenML-CC18 (test)
82.31AccuracySubTab w/ Dropout
Evaluation Results
| Method | Links | |
|---|---|---|
| SubTab w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 82.31 | |
| SubTabArchitecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 82.11 | |
| AE w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 81.54 | |
| Autoencoder (AE)Architecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 81.32 | |
| Logistic RegressionEvaluation protocol=Raw features2021.10 | 76.09 | |
| VIME-selfArchitecture=[256, 256, 256, 256], Evaluation protocol=Logistic regression on embeddings2021.10 | 73.92 |