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| author | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-01-10 11:44:54 +0100 |
|---|---|---|
| committer | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-01-10 11:44:54 +0100 |
| commit | e2f1f5d08e8e032d917cb2a7ba329db1bee9c2ee (patch) | |
| tree | 021edc75974d62f9fadc7c18401a922b9cb445f8 /lib/parameters.py | |
| parent | 0c3f350a577cfb1b36d45707ae3f36c2fe0d46ba (diff) | |
Expose more XGBoost training hyper-parameters via environment variables
Diffstat (limited to 'lib/parameters.py')
| -rw-r--r-- | lib/parameters.py | 8 |
1 files changed, 5 insertions, 3 deletions
diff --git a/lib/parameters.py b/lib/parameters.py index 74f1007..bc0d2a1 100644 --- a/lib/parameters.py +++ b/lib/parameters.py @@ -1087,9 +1087,11 @@ class ModelAttribute: xgb = xgboost.XGBRegressor( n_estimators=int(os.getenv("DFATOOL_XGB_N_ESTIMATORS", "100")), max_depth=int(os.getenv("DFATOOL_XGB_MAX_DEPTH", "10")), - subsample=0.7, - gamma=0.01, - reg_alpha=0.0006, + subsample=float(os.getenv("DFATOOL_XGB_SUBSAMPLE", "0.7")), + eta=float(os.getenv("DFATOOL_XGB_ETA", "0.3")), + gamma=float(os.getenv("DFATOOL_XGB_GAMMA", "0.01")), + reg_alpha=float(os.getenv("DFATOOL_XGB_REG_ALPHA", "0.0006")), + reg_lambda=float(os.getenv("DFATOOL_XGB_REG_LAMBDA", "1")), ) fit_parameters, category_to_index, ignore_index = param_to_ndarray( parameters, with_nan=False, categorial_to_scalar=categorial_to_scalar |