Text Classification on Emotion multi-class (five random splits)
0.152NLLBinwise-Vector
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| Binwise-VectorK (clusters)=-, λ (shrinkage)=-2025.10 | 0.152 | 0.086 | 0.017 | 93.2 | |
| Binwise-TSK (clusters)=-, λ (shrinkage)=-2025.10 | 0.156 | 0.086 | 0.016 | 93.4 | |
| VectorK (clusters)=25, λ (shrinkage)=12025.10 | 0.157 | 0.087 | 0.027 | 93.5 | |
| VectorK (clusters)=-, λ (shrinkage)=-2025.10 | 0.158 | 0.088 | 0.027 | 93.5 | |
| TSK (clusters)=-, λ (shrinkage)=-2025.10 | 0.158 | 0.088 | 0.028 | 93.5 | |
| DirichletK (clusters)=-, λ (shrinkage)=-2025.10 | 0.159 | 0.088 | 0.028 | 93.2 | |
| TSK (clusters)=25, λ (shrinkage)=12025.10 | 0.16 | 0.087 | 0.03 | 93.5 | |
| DirichletK (clusters)=25, λ (shrinkage)=12025.10 | 0.162 | 0.087 | 0.031 | 93.2 | |
| BaseK (clusters)=-, λ (shrinkage)=-2025.10 | 0.167 | 0.093 | 0.032 | 93.5 |