Table 1 In each run, a random combination of hyperparameters is tested
From: Load forecasting for energy communities: a novel LSTM-XGBoost hybrid model based on smart meter data
Hyperparameter | Value |
|---|---|
Past input timesteps as multiple of K | 1, 2, 3 |
Batch size | 32, 64 |
Epochs | 50, 75, 100 |
Steps per epoch | 75, 100, 125, 150, 200 |
Learning rate | 0.1, 0.01, 0.005, 0.001 |
Number of units in LSTM-layer | 20, 70, 130, 200, 260 |
Number of units in dense layers | 20, 70, 130, 200, 260 |