更新 function.py

function.py

@@ -1,6 +1,7 @@
 # function.py
 import numpy as np
 from sklearn.preprocessing import StandardScaler
+from itertools import product
 
 """
 实验说明:
@@ -28,7 +29,7 @@ name = "程悦"
 def sigmoid(z):
     return 1.0 / (1 + np.exp(-z))
 
-def train_logreg(X, y, learning_rate=0.01, iterations=1000, batch_size=32, regularization=None, lambda_reg=0.1):
+def train_logreg(X, y, learning_rate=0.01, iterations=1000, batch_size=16, regularization=L1, lambda_reg=0.1):
     """
     对率回归训练函数。
 
@@ -129,8 +130,7 @@ if __name__ == "__main__":
     X_test, y_test = load_data("./data/horse-colic.test")
 
     # 训练对率回归模型
-    weights = train_logreg(X_train, y_train, learning_rate=0.01, iterations=1000, batch_size=32, regularization='L2',
-                           lambda_reg=0.1)
+    weights = train_logreg(X_train, y_train)
 
     # 测试单个数据
     y_pred = predict_logreg(X_test[11], weights)