Time Series Classification On Wafer
Metrics
Accuracy
NLL
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy | NLL |
|---|---|---|
| variational-gaussian-processes-with-signature | 0.966 | 0.105 |
| multivariate-lstm-fcns-for-time-series | 0.99 | - |
| seq2tens-an-efficient-representation-of | 0.981 | - |
| variational-gaussian-processes-with-signature | 0.994 | 0.029 |
| variational-gaussian-processes-with-signature | 0.978 | 0.081 |
| variational-gaussian-processes-with-signature | 0.965 | 0.105 |
| variational-gaussian-processes-with-signature | 0.984 | 0.085 |
| seq2tens-an-efficient-representation-of | 0.989 | - |
| variational-gaussian-processes-with-signature | 0.988 | 0.048 |
| convolutional-shapelet-transform-a-new | 0.9999513303049968 | - |