更新 function.py

function.py

@@ -47,6 +47,10 @@ def train_logreg(X, y, learning_rate=0.01, iterations=1000):
         z = np.dot(X, weights)
         predictions = 1 / (1 + np.exp(-z))
         gradient = np.dot(X.T, (predictions - y)) / m
+        
+        # L2正则化
+        gradient += (lambda_reg / m) * weights
+
         weights -= learning_rate * gradient
 
     return weights