Time Series Classification On Japanesevowels
Metrics
Accuracy
NLL
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy | NLL |
|---|---|---|
| variational-gaussian-processes-with-signature | 0.981 | 0.080 |
| variational-gaussian-processes-with-signature | 0.982 | 0.069 |
| variational-gaussian-processes-with-signature | 0.986 | 0.067 |
| variational-gaussian-processes-with-signature | 0.982 | 0.061 |
| variational-gaussian-processes-with-signature | 0.985 | 0.053 |
| variational-gaussian-processes-with-signature | 0.986 | 0.052 |
| multivariate-lstm-fcns-for-time-series | 0.99 | - |
| seq2tens-an-efficient-representation-of | 0.979 | - |
| seq2tens-an-efficient-representation-of | 0.980 | - |
| improving-position-encoding-of-transformers | 0.9891 | - |