| seed: 2019 | |
| data: | |
| path: data/meteonorm_rf_hourly.npz | |
| synthetic_days: 30 | |
| start_day_of_year: 1 | |
| stations: 12 | |
| pollutants: [PM2.5, PM10, NO2, SO2, O3, CO] | |
| frequency: hourly | |
| train_fraction: 0.70 | |
| model: | |
| engineering: | |
| trees: 12 | |
| max_depth: 8 | |
| min_samples_leaf: 8 | |
| max_features: sqrt | |
| split_candidates: 12 | |
| paper_protocol: | |
| trees: hundreds | |
| normalization_resamples: 1000 | |
| normalization: | |
| engineering_resamples: 32 | |
| season_window_days: 14 | |
| match_hour: true | |
| preserve_time_features: [ttrend, day_of_year, weekend, hour] | |
| paths: | |
| checkpoint: result/checkpoints/meteonorm_rf.pkl | |
| training_metrics: result/training/metrics.json | |
| inference: result/output/predictions.npz | |
| evaluation_dir: result/evaluation | |