Classification on Glass LDLSS
81.32AccuracyCatBoost
Evaluation results
| Method | Links | |
|---|---|---|
| CatBoost2026.05 | 81.32 | |
| TabPFN v22026.05 | 80.82 | |
| Random Forest2026.05 | 78.51 | |
| LGBM2026.05 | 78.49 | |
| GBM2026.05 | 75.7 | |
| FT-Transformer2026.05 | 75.68 | |
| ModernNCA2026.05 | 75.68 | |
| XGBoost2026.05 | 75.23 | |
| AdaBoost2026.05 | 75.2 | |
| DynaTab2026.05 | 75.01 | |
| TabR2026.05 | 72.43 | |
| TabPFN2026.05 | 71.94 | |
| NODE2026.05 | 71.48 | |
| LLSPIN2026.05 | 70.54 | |
| Decision Tree2026.05 | 69.62 | |
| DeepFM2026.05 | 69.61 | |
| INVASE2026.05 | 69.14 | |
| SVM2026.05 | 68.69 | |
| SAINT2026.05 | 68.18 | |
| REAL-X2026.05 | 68.18 | |
| MLP2026.05 | 67.26 | |
| TabNet2026.05 | 66.82 | |
| TabTransformer2026.05 | 66.82 | |
| LSPIN2026.05 | 65.88 | |
| TabSeq2026.05 | 65.42 | |
| TabulaRNN2026.05 | 65.39 | |
| Mambular2026.05 | 64.95 | |
| KNN2026.05 | 64.43 | |
| DANets2026.05 | 63.54 | |
| Trompt2026.05 | 63.1 | |
| AutoInt2026.05 | 62.62 | |
| TANGOS2026.05 | 62.15 | |
| CategoryEmbedding2026.05 | 62.13 | |
| STG2026.05 | 61.66 | |
| MambAttention2026.05 | 61.16 | |
| NDTF2026.05 | 60.26 | |
| Lasso2026.05 | 59.32 | |
| MambaTab2026.05 | 57.94 | |
| 1-D CNN2026.05 | 57.48 | |
| ResNetTabular2026.05 | 57.01 | |
| L2X2026.05 | 56.53 | |
| DCN2026.05 | 56.08 | |
| ENODE2026.05 | 51.45 | |
| TabM2026.05 | 48.54 | |
| Naive Bayes2026.05 | 44.85 | |
| ProtoGate2026.05 | 31.3 |