perf(qav3): fine tune n_estimators HPO step

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py
index 5d476ec6b8aa6e091c04c2095ac2f94c27fd7a33..0916456f84117d03190e1e32cfe7f7ec8aae522b 100644 (file)
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py
@@ -647,7 +647,7 @@ def hp_objective(
     model_training_parameters,
 ) -> float:
     study_parameters = {
-        "n_estimators": trial.suggest_int("n_estimators", 100, 2000, step=10),
+        "n_estimators": trial.suggest_int("n_estimators", 100, 2000, step=100),
         "num_leaves": trial.suggest_int("num_leaves", 2, 256),
         "learning_rate": trial.suggest_float("learning_rate", 1e-3, 0.3, log=True),
         "min_child_samples": trial.suggest_int("min_child_samples", 5, 100),

diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV3.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV3.py
index e860c48e30a3aac686d0c8db09d637333e2388ed..244c575c9fffa77469b265aa61194a8f1cff5eef 100644 (file)
--- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV3.py
+++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV3.py
@@ -655,7 +655,7 @@ def hp_objective(
     model_training_parameters,
 ) -> float:
     study_parameters = {
-        "n_estimators": trial.suggest_int("n_estimators", 100, 2000, step=10),
+        "n_estimators": trial.suggest_int("n_estimators", 100, 2000, step=100),
         "learning_rate": trial.suggest_float("learning_rate", 1e-3, 0.3, log=True),
         "max_depth": trial.suggest_int("max_depth", 3, 18),
         "min_child_weight": trial.suggest_int("min_child_weight", 1, 200),