perf(qav3): add n_estimators to HPO

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

diff --git a/quickadapter/user_data/config-template.json b/quickadapter/user_data/config-template.json
index 80e5eae93f79bd32fe63da8c1e02c3394dff351f..47dea6e403295fc05d58d8a229261bdde1f66d70 100644 (file)
--- a/quickadapter/user_data/config-template.json
+++ b/quickadapter/user_data/config-template.json
@@ -177,7 +177,6 @@
       // "device": "gpu",
       // "use_rmm:": true,
       "n_jobs": 6, // set to number of CPU threads / 4
-      "n_estimators": 1000,
       "verbosity": 1
     }
   },

diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py
index 535052235e30034f33b0c3c2089acf7d0e0580c1..5d476ec6b8aa6e091c04c2095ac2f94c27fd7a33 100644 (file)
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV3.py
@@ -43,7 +43,7 @@ class LightGBMRegressorQuickAdapterV3(BaseRegressionModel):
     https://github.com/sponsors/robcaulk
     """
 
-    version = "3.6.0"
+    version = "3.6.1"
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
@@ -647,6 +647,7 @@ def hp_objective(
     model_training_parameters,
 ) -> float:
     study_parameters = {
+        "n_estimators": trial.suggest_int("n_estimators", 100, 2000, step=10),
         "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 c96fcddcd6678399bbf24c5ed6bb36f3371f9574..e860c48e30a3aac686d0c8db09d637333e2388ed 100644 (file)
--- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV3.py
+++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV3.py
@@ -43,7 +43,7 @@ class XGBoostRegressorQuickAdapterV3(BaseRegressionModel):
     https://github.com/sponsors/robcaulk
     """
 
-    version = "3.6.0"
+    version = "3.6.1"
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
@@ -655,6 +655,7 @@ def hp_objective(
     model_training_parameters,
 ) -> float:
     study_parameters = {
+        "n_estimators": trial.suggest_int("n_estimators", 100, 2000, step=10),
         "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),