Benchmark 5d9e6e63cbf0
| Parameter | Value |
|---|---|
| Benchmark hash | 5d9e6e63cbf0 |
| Original paper | https://doi.org/10.48550/arXiv.2503.17410 |
| Dataset | CESNET-TimeSeries24 |
| Aggregation | AGG_1_HOUR |
| Source | INSTITUTION_SUBNETS |
| Type | Time-Based |
| Train size | 0.35 |
| Val size | 0.05 |
| Test size | 0.6 |
| Uni/Multi variate | Univariate |
| Metrics | n_bytes |
| Default value | 0 |
| Filler | None |
| Transformer | MinMaxScaler |
| Anomaly handler | None |
| Sliding window train | 168 |
| Sliding window prediction | 24 |
| Sliding window step | 24 |
| Set shared size | 168 |
| TS IDs | 1.0 |
| Related work | Model | Average RMSE | Std RMSE | Average R2-score | Std R2-score |
|---|---|---|---|---|---|
| https://arxiv.org/abs/2503.17410 | GRU | 0.237 | 1.15 | -0.55 | 1.4 |
| https://arxiv.org/abs/2503.17410 | GRU_FCN | 0.229 | 1.15 | -0.27 | 1.1 |
| https://arxiv.org/abs/2503.17410 | INCEPTIONTIME | 0.59 | 1.1 | -8.9 | 2.7 |
| https://arxiv.org/abs/2503.17410 | LSTM | 0.237 | 1.15 | -0.53 | 1.3 |
| https://arxiv.org/abs/2503.17410 | LSTM_FCN | 0.231 | 1.15 | -0.55 | 1.8 |
| https://arxiv.org/abs/2503.17410 | MEAN | 0.394 | 1.66 | 0.05 | 0.1 |
| https://arxiv.org/abs/2503.17410 | RCLSTM | 0.334 | 1.48 | -0.64 | 1.9 |
| https://arxiv.org/abs/2503.17410 | RESNET | 0.244 | 1.15 | -0.77 | 1.6 |