更新 function.py

function.py

@@ -1,5 +1,6 @@
 import numpy as np
 import os
+from sklearn.preprocessing import StandardScaler  # 导入标准化库
 
 # 学号和姓名
 id = "202210423130"
@@ -107,6 +108,10 @@ if __name__ == "__main__":
         print(e)
         exit()
 
+    # 数据归一化处理
+    scaler = StandardScaler()
+    X_train = scaler.fit_transform(X_train)  # 使用训练集进行标准化
+
     # k折交叉验证
     avg_accuracy = k_fold_cross_validation(X_train, y_train, k=5, learning_rate=0.01, iterations=1000)
     print(f"K折交叉验证的平均准确率: {avg_accuracy:.4f}")
@@ -118,6 +123,9 @@ if __name__ == "__main__":
         print(e)
         exit()
 
+    # 测试集也需要进行相同的归一化
+    X_test = scaler.transform(X_test)  # 使用相同的Scaler进行测试集的标准化
+
     # 训练对率回归模型
     weights = train_logreg(X_train, y_train, learning_rate=0.01, iterations=1000)