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Implemented the plotting of ensemble methods with model contributions #789

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2d9ca91
Implemented the plotting of ensemble methods with model contributions…
Guilly-Kolkman Dec 17, 2025
103c3df
Merge branch 'research/HybridForecaster2.0' into model_contribution
Guilly-Kolkman Dec 17, 2025
cea9038
Fixed typing issues in model_contributions_plot.py
Guilly-Kolkman Dec 17, 2025
2d61aaf
Fixed typing issue
Guilly-Kolkman Dec 17, 2025
9c6368d
FixedD-1T06:00 sanitization for handling on windows paths
Guilly-Kolkman Dec 18, 2025
3cfc37c
Deleted notebook for original plotting code
Guilly-Kolkman Dec 18, 2025
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1 change: 1 addition & 0 deletions data/liander2024-energy-forecasting-benchmark
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Submodule liander2024-energy-forecasting-benchmark added at ec2863
16 changes: 12 additions & 4 deletions examples/benchmarks/liander_2024_ensemble.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,12 +42,15 @@
N_PROCESSES = 1 if True else multiprocessing.cpu_count() # Amount of parallel processes to use for the benchmark

ensemble_type = "learned_weights" # "stacking", "learned_weights" or "rules"
base_models = ["lgbm", "gblinear"] # combination of "lgbm", "gblinear", "xgboost" and "lgbm_linear"
base_models = [
"lgbm",
"gblinear",
] # combination of "lgbm", "gblinear", "xgboost" and "lgbm_linear"
combiner_model = (
"lgbm" # "lgbm", "xgboost", "rf" or "logistic" for learned weights combiner, gblinear for stacking combiner
)

model = "Ensemble_" + "_".join(base_models) + "_" + ensemble_type + "_" + combiner_model
model = "Ensemble_contributions_" + "_".join(base_models) + "_" + ensemble_type + "_" + combiner_model

# Model configuration
FORECAST_HORIZONS = [LeadTime.from_string("PT36H")] # Forecast horizon(s)
Expand Down Expand Up @@ -90,7 +93,12 @@
relative_humidity_column="relative_humidity_2m",
energy_price_column="EPEX_NL",
forecast_combiner_sample_weight_exponent=0,
forecaster_sample_weight_exponent={"gblinear": 1, "lgbm": 0, "xgboost": 0, "lgbm_linear": 0},
forecaster_sample_weight_exponent={
"gblinear": 1,
"lgbm": 0,
"xgboost": 0,
"lgbm_linear": 0,
},
)


Expand All @@ -111,7 +119,7 @@
start_time = time.time()
create_liander2024_benchmark_runner(
storage=LocalBenchmarkStorage(base_path=OUTPUT_PATH / model),
data_dir=Path("../data/liander2024-energy-forecasting-benchmark"),
data_dir=Path("data/liander2024-energy-forecasting-benchmark"),
callbacks=[StrictExecutionCallback()],
).run(
forecaster_factory=create_openstef4_preset_backtest_forecaster(
Expand Down
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