更新 function.py

function.py

@@ -28,7 +28,7 @@ name = "程悦"
 def sigmoid(z):
     return 1.0 / (1 + np.exp(-z))
 
-def train_logreg(X, y, learning_rate=0.01, iterations=1000):
+def train_logreg(X, y, learning_rate=0.01, iterations=1000, regularization='l2', lambda_=0.01):
     """
     对率回归训练函数。
 
@@ -45,6 +45,13 @@ def train_logreg(X, y, learning_rate=0.01, iterations=1000):
         z = np.dot(X, weights)
         h = sigmoid(z)
         gradient = np.dot(X.T, (h - y)) / m
+        
+        # 正则化
+        if regularization == 'l2':
+            gradient += lambda_ * weights / m
+        elif regularization == 'l1':
+            gradient += lambda_ * np.sign(weights) / m
+        
         weights -= learning_rate * gradient
     return weights