diff --git a/bluecast/blueprints/cast_cv.py b/bluecast/blueprints/cast_cv.py
index f5a4e1e6..f5791eaf 100644
--- a/bluecast/blueprints/cast_cv.py
+++ b/bluecast/blueprints/cast_cv.py
@@ -320,8 +320,17 @@ def predict(
             if return_sub_models_preds:
                 return result_df.loc[:, prob_cols], result_df.loc[:, class_cols]
             else:
+                if self.conf_params_xgboost:
+                    classification_threshold = (
+                        self.conf_params_xgboost.classification_threshold
+                    )
+                else:
+                    classification_threshold = 0.5
+
                 y_probs = result_df.loc[:, prob_cols].mean(axis=1)
-                y_classes = (result_df.loc[:, prob_cols].mean(axis=1) > 0.5).astype(int)
+                y_classes = (
+                    result_df.loc[:, prob_cols].mean(axis=1) > classification_threshold
+                ).astype(int)
 
                 if (
                     self.bluecast_models[0].feat_type_detector
diff --git a/bluecast/blueprints/custom_model_recipes.py b/bluecast/blueprints/custom_model_recipes.py
index c70f3078..32d27767 100644
--- a/bluecast/blueprints/custom_model_recipes.py
+++ b/bluecast/blueprints/custom_model_recipes.py
@@ -82,7 +82,7 @@ def predict(self, df: pd.DataFrame) -> Tuple[PredictedProbas, PredictedClasses]:
 class LinearRegressionModel(BaseClassMlModel):
     def __init__(self):
         self.linear_regression_model: LinearRegression = LinearRegression()
-        self.model: Optional[GridSearchCV] = None
+        self.model: Optional[LinearRegression] = None
 
     def autotune(
         self,
@@ -106,7 +106,7 @@ def fit(
 
     def predict(self, df: pd.DataFrame) -> Tuple[PredictedProbas, PredictedClasses]:
 
-        if isinstance(self.model, GridSearchCV):
+        if isinstance(self.model, LinearRegression):
             preds = self.model.predict(df)
             return preds
         else:
diff --git a/dist/bluecast-1.6.0-py3-none-any.whl b/dist/bluecast-1.6.0-py3-none-any.whl
index 63ea3699..f42a8e90 100644
Binary files a/dist/bluecast-1.6.0-py3-none-any.whl and b/dist/bluecast-1.6.0-py3-none-any.whl differ
diff --git a/dist/bluecast-1.6.0.tar.gz b/dist/bluecast-1.6.0.tar.gz
index 9653ca1b..5f7dea93 100644
Binary files a/dist/bluecast-1.6.0.tar.gz and b/dist/bluecast-1.6.0.tar.gz differ
diff --git a/kaggle_competition_code_repository/kaggle_automl_competition_august_2024.py b/kaggle_competition_code_repository/kaggle_automl_competition_august_2024.py
index 63cd82b3..7f83aba4 100644
--- a/kaggle_competition_code_repository/kaggle_automl_competition_august_2024.py
+++ b/kaggle_competition_code_repository/kaggle_automl_competition_august_2024.py
@@ -72,7 +72,7 @@ def replace_diff_values(x, diff_values=diff_values):
         train_config.calculate_shap_values = False
     else:
         train_config.autotune_model = True
-        train_config.hypertuning_cv_folds = 1
+        train_config.hypertuning_cv_folds = 5
         train_config.hypertuning_cv_repeats = 1
         train_config.cardinality_threshold_for_onehot_encoding = 3
         train_config.hyperparameter_tuning_rounds = 50