diff --git a/function.py b/function.py
index 9cc2ab4..f77b360 100644
--- a/function.py
+++ b/function.py
@@ -34,16 +34,27 @@ def load_data(filepath):
     - np.array: 特征数据。
     - np.array: 标签数据。
     """
-    # Load the data, treating missing values as NaN
     try:
+        # Load data with genfromtxt, filling missing values with NaN
         data = np.genfromtxt(filepath, delimiter=',', missing_values='?', filling_values=np.nan)
         
+        # Check if the data has been loaded correctly with at least two dimensions
+        if data.ndim < 2:
+            print(f"Error: File '{filepath}' may be empty or improperly formatted.")
+            return None, None
+
         # Remove rows with NaN values
         data = data[~np.isnan(data).any(axis=1)]
         
-        # Split into features and labels
+        # Ensure there's still data left after removing rows with NaN
+        if data.size == 0:
+            print(f"Error: No valid data after removing NaN rows in file '{filepath}'.")
+            return None, None
+
+        # Split into features (X) and labels (y)
         X = data[:, :-1]  # Features
         y = data[:, -1]   # Labels
+        
         return X, y
     except Exception as e:
         print(f"Error loading data: {e}")
@@ -100,4 +111,3 @@ def predict_logreg(X, weights):
     X = np.c_[np.ones(X.shape[0]), X]  # Add intercept term
     probabilities = sigmoid(np.dot(X, weights))
     return (probabilities >= 0.5).astype(int)
-