更新 function.py

function.py

@@ -31,7 +31,7 @@ import numpy as np
 def sigmoid(z):
     return 1 / (1 + np.exp(-z))
 
-def train_logreg(X, y, learning_rate=0.01, iterations=1000):
+def train_logreg(X, y, learning_rate=0.001, iterations=2000):
     """
     对率回归训练函数。
 
@@ -105,7 +105,7 @@ 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=0.001, iterations=1000)  # 修改学习率
+    weights = train_logreg(X_train, y_train, learning_rate=0.001, iterations=2000)  # 修改迭代次数
 
     # 测试单个数据
     y_pred = predict_logreg(X_test[11], weights)