Time Series Classification on FordA (test)
96.5AccuracyST
Evaluation results
| Method | Links | |
|---|---|---|
| ST2019.09 | 96.5 | |
| PARALESN (DEEP)Number of recurrent neurons=1024, Architecture=Deep2026.01 | 92.8 | |
| GENDISclassifier=Ensemble2019.09 | 90.8 | |
| GENDISclassifier=Logistic Regression2019.09 | 90.7 | |
| ESN (DEEP)Number of recurrent neurons=1024, Architecture=Deep2026.01 | 90.1 | |
| LTS2019.09 | 89.5 | |
| ResRMNIRecurrent Matrix=Identity2025.08 | 88.9 | |
| PARALESNNumber of recurrent neurons=1024, Architecture=Shallow2026.01 | 83.4 | |
| RMN2025.08 | 82.8 | |
| FS2019.09 | 78.5 | |
| ESNNumber of recurrent neurons=1024, Architecture=Shallow2026.01 | 75.8 | |
| LeakyESN2025.08 | 69 | |
| ResESNIRecurrent Matrix=Identity2025.08 | 68.6 | |
| ResESNCRecurrent Matrix=Circular2025.08 | 65 | |
| ResRMNRRecurrent Matrix=Random2025.08 | 64.5 | |
| ResESNRRecurrent Matrix=Random2025.08 | 63.8 | |
| ResRMNCRecurrent Matrix=Circular2025.08 | 59.1 |