更新 function.py

function.py

@@ -35,16 +35,13 @@ def load_data(filepath):
     y = data[:, -1]
     return X, y
 
-def train_logreg(X, y, initial_learning_rate=0.1, iterations=1000, decay_rate=0.01):
-    """训练逻辑回归模型，使用随机梯度下降和学习率衰减."""
+def train_logreg(X, y, learning_rate=0.1, iterations=1000):
+    """训练逻辑回归模型，使用随机梯度下降."""
     n_samples, n_features = X.shape
     weights = np.zeros(n_features + 1)  # 增加一位用于偏置
     X = np.c_[X, np.ones((n_samples, 1))]  # 增加偏置项
 
-    for i in range(iterations):
-        # 更新学习率
-        learning_rate = initial_learning_rate / (1 + decay_rate * i)
-
+    for _ in range(iterations):
         random_index = np.random.randint(n_samples)
         X_i = X[random_index]
         y_i = y[random_index]