Time Series Classification On Japanesevowels
Métriques
Accuracy
NLL
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
Nom du modèle | 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 | - |