diff --git a/mlforecast/auto.py b/mlforecast/auto.py
index 96e30b61..74f3929c 100644
--- a/mlforecast/auto.py
+++ b/mlforecast/auto.py
@@ -102,7 +102,7 @@ def random_forest_space(trial: optuna.Trial):
     return {
         "n_estimators": trial.suggest_int("n_estimators", 50, 1000),
         "max_depth": trial.suggest_int("max_depth", 1, 10),
-        "min_samples_split": trial.suggest_int("min_child_samples", 1, 100),
+        "min_samples_split": trial.suggest_int("min_samples_split", 2, 100),
         "max_features": trial.suggest_float("max_features", 0.5, 1.0),
         "criterion": trial.suggest_categorical(
             "criterion", ["squared_error", "absolute_error"]
diff --git a/nbs/auto.ipynb b/nbs/auto.ipynb
index dcda602e..2d9073f9 100644
--- a/nbs/auto.ipynb
+++ b/nbs/auto.ipynb
@@ -134,7 +134,7 @@
     "    return {\n",
     "        'n_estimators': trial.suggest_int('n_estimators', 50, 1000),\n",
     "        'max_depth': trial.suggest_int('max_depth', 1, 10),\n",
-    "        'min_samples_split': trial.suggest_int('min_child_samples', 1, 100),\n",
+    "        'min_samples_split': trial.suggest_int('min_samples_split', 2, 100),\n",
     "        'max_features': trial.suggest_float('max_features', 0.5, 1.0),\n",
     "        'criterion': trial.suggest_categorical('criterion', ['squared_error', 'absolute_error']),\n",
     "    }\n",