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, regularization='l2', lambda_=0.01):
+def train_logreg(X, y, learning_rate=0.01, iterations=1000):
     """
     对率回归训练函数。
 
@@ -45,13 +45,6 @@ def train_logreg(X, y, learning_rate=0.01, iterations=1000, regularization='l2',
         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