更新 function.py

function.py

@@ -32,8 +32,8 @@ def sigmoid(z):
     """计算sigmoid函数"""
     return 1 / (1 + np.exp(-z))
 
-def train_logreg(X, y, learning_rate=0.01, iterations=1000, 2_penalty=0.01):
-    """对率回归训练函数。"""
+def train_logreg(X, y, learning_rate=0.01, iterations=1000, l2_penalty=0.01):
+    """对率回归训练函数，包括L2正则化。"""
     weights = np.zeros(X.shape[1])
     
     for _ in range(iterations):
@@ -44,6 +44,7 @@ def train_logreg(X, y, learning_rate=0.01, iterations=1000, 2_penalty=0.01):
     
     return weights
 
+
 def predict_logreg(X, weights):
     """使用训练好的权重预测标签"""
     z = np.dot(X, weights)