diff --git a/function.py b/function.py
index bc959e9..a352d84 100644
--- a/function.py
+++ b/function.py
@@ -1,6 +1,5 @@
 # function.py
 import numpy as np
-from scipy.optimize import minimize
 """
 实验说明:
 - 自行编写实现数据加载与预测病马死亡的对率回归算法。
@@ -95,4 +94,19 @@ def predict_logreg(inX, weights):
     """
     inX = np.c_[1, inX]  # 添加截距项
     prob = sigmoid(np.dot(inX, weights))
-    return 1 if prob > 0.5 else 0
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+    return 1 if prob > 0.5 else 0
+
+# 移除以下测试代码，仅在本地测试时使用
+# if __name__ == "__main__":
+#     # 加载训练集
+#     X_train, y_train = load_data("./data/horse-colic.data")
+#
+#     # 加载测试集
+#     X_test, y_test = load_data("./data/horse-colic.test")
+#
+#     # 训练对率回归模型
+#     weights = train_logreg(X_train, y_train)
+#
+#     # 测试单个数据
+#     y_pred = predict_logreg(X_test[11], weights)
+#     print(f"预测结果: {y_pred}, 实际结果: {int(y_test[11])}")
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