| { |
| "model_name": "ML-MODIS", |
| "model_type": "ml_modis", |
| "architectures": ["BootstrapRandomForestRegressor"], |
| "framework": "PyTorch", |
| "domain": "earth-science", |
| "task": "counterfactual-cloud-property-regression", |
| "implementation": { |
| "entry_point": "model/ml_modis.py", |
| "scope": "independent paper-method engineering reproduction", |
| "train_script": "scripts/train.py", |
| "inference_script": "scripts/inference.py", |
| "evaluation_script": "scripts/result.py", |
| "synthetic_data_script": "scripts/fake_data.py" |
| }, |
| "architecture": { |
| "family": "bootstrap random regression forest", |
| "input_features": 114, |
| "output_targets": 4, |
| "independent_models": 8, |
| "months": [9, 10], |
| "targets": ["Nd", "reff", "LWP", "CF"] |
| }, |
| "data": { |
| "format": "NPZ", |
| "protocol": "ml_modis_npz_v1", |
| "input_shape": ["N", 114], |
| "target_shape": ["N", 4], |
| "alignment_key": ["year", "month", "platform", "latitude", "longitude"] |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/ml_modis.py", |
| "scripts/fake_data.py", |
| "scripts/train.py", |
| "scripts/inference.py", |
| "scripts/result.py" |
| ] |
| } |
|
|
