CyanoHAB Intensity Forecasting on CyanoHAB intensity forecasting 2023-2024 (test)
78.94AccuracyTransformer-BiLSTM
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| Transformer-BiLSTMModel Category=Deep Learning2025.12 | 78.94 | 78.8 | 78.94 | 78.86 | 82.55 | |
| Transformer-GRUModel Category=Deep Learning2025.12 | 77.95 | 78.43 | 77.95 | 78.13 | 82.53 | |
| BiLSTMModel Category=Deep Learning2025.12 | 77.71 | 77.38 | 77.71 | 77.46 | 80.32 | |
| Transformer-LSTMModel Category=Deep Learning2025.12 | 77.47 | 77.39 | 77.47 | 77.43 | 80.85 | |
| Transformer-BiGRUModel Category=Deep Learning2025.12 | 77.13 | 76.97 | 77.13 | 77.04 | 81.01 | |
| Transformer-C.AttentionModel Category=Deep Learning2025.12 | 75.08 | 74.48 | 75.08 | 74.3 | 77.04 | |
| TransformerModel Category=Deep Learning2025.12 | 74.95 | 74.35 | 74.95 | 74.08 | 77.18 | |
| Persistence ModelModel Category=Baseline2025.12 | 71.34 | 71.68 | 71.34 | 71.54 | 70.42 | |
| Random ForestModel Category=Machine Learning2025.12 | 45.45 | 63.38 | 57.89 | 59.36 | 82.11 | |
| Support Vector MachinesModel Category=Machine Learning2025.12 | 43.29 | 62.2 | 51.91 | 55.29 | 80.12 | |
| XGBoostModel Category=Machine Learning2025.12 | 41.77 | 61.22 | 53.67 | 56.68 | 80.16 |