Classification on Dataset-4 OpenML-CC18 (test)
94.85AccuracySubTab w/ Dropout
Evaluation Results
| Method | Links | |
|---|---|---|
| SubTab w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 94.85 | |
| Autoencoder (AE)Architecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 94.84 | |
| SubTabArchitecture=[256, 256, 256, 256], Dropout (p)=0, Evaluation protocol=Logistic regression on embeddings2021.10 | 94.74 | |
| AE w/ DropoutArchitecture=[256, 256, 256, 256], Dropout (p)=0.04, Evaluation protocol=Logistic regression on embeddings2021.10 | 94.69 | |
| VIME-selfArchitecture=[256, 256, 256, 256], Evaluation protocol=Logistic regression on embeddings2021.10 | 94.28 | |
| Logistic RegressionEvaluation protocol=Raw features2021.10 | 94.01 |