fix: handle case where scikit model output not provided

Author: jlwalke2

src/sasctl/utils/model_info.py

@@ -313,14 +313,22 @@ class SklearnModelInfo(ModelInfo):
     }
 
     def __init__(self, model, X, y):
-        # Ensure input/output is a DataFrame for consistency
-        X_df = pd.DataFrame(X)
-        y_df = pd.DataFrame(y)
+
 
         is_classifier = hasattr(model, "classes_")
         is_binary_classifier = is_classifier and len(model.classes_) == 2
         is_clusterer = hasattr(model, "cluster_centers_")
 
+        if y is None:
+            if hasattr(model, "predict_proba"):
+                y = model.predict_proba(X)
+            else:
+                y = model.predict(X)
+
+        # Ensure input/output is a DataFrame for consistency
+        X_df = pd.DataFrame(X)
+        y_df = pd.DataFrame(y)
+
         # If not a classfier or a clustering algorithm and output is a single column, then
         # assume its a regression algorithm
         is_regressor = not is_classifier and not is_clusterer and (y_df.shape[1] == 1 or "Regress" in type(model).__name__)