refactor: ensure metric rmse is used as LightGBM optuna metric

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

diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
index b7540a40039a221aebf2f10dcb2e3462f89b4be5..5fe43c6cdcb23708524d7db5c29a55757df6577e 100644 (file)
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
@@ -243,6 +243,7 @@ def objective(trial, X, y, weights, X_test, y_test, params):
         y,
         sample_weight=weights,
         eval_set=[(X_test, y_test)],
+        eval_metric="rmse",
         callbacks=[optuna.integration.LightGBMPruningCallback(trial, "rmse")],
     )
     y_pred = model.predict(X_test)