diff --git a/function.py b/function.py
index 6c65625..d333be7 100644
--- a/function.py
+++ b/function.py
@@ -66,6 +66,8 @@ def predict_logreg(inX, weights):
     prediction = 1 / (1 + np.exp(-np.dot(inX, weights)))
     return 1 if prediction > 0.5 else 0
 
+import numpy as np
+
 def load_data(filepath):
     """
     从文件中加载数据，若不自行正确实现，则无法通过评测，**不记录成绩**。
@@ -78,18 +80,18 @@ def load_data(filepath):
     - np.array: 标签数据。
     """
     # 读取数据，将非数值转换为NaN
-    data = np.genfromtxt(filepath, delimiter=',', dtype=float, missing_values='?')
+    data = np.genfromtxt(filepath, delimiter=' ', dtype=float, missing_values='?')
 
     # 分离特征和标签
     X = data[:, :-1]
     y = data[:, -1]
 
-    # 将缺失值填充为列的平均值
-    for i in range(X.shape[1]):
-        X[:, i] = np.where(np.isnan(X[:, i]), np.nanmean(X[:, i]), X[:, i])
+    # 将缺失值填充为0
+    X[np.isnan(X)] = 0
 
     return X, y.astype(int)
 
+
 if __name__ == "__main__":
     # 以下代码可用于测试，可自行随意修改
     # 加载训练集