更新 function.py

function.py

@@ -95,18 +95,4 @@ def predict_logreg(inX, weights):
     """
     inX = np.c_[1, inX]  # 添加截距项
     prob = sigmoid(np.dot(inX, weights))
-    return 1 if prob > 0.5 else 0
+    return 1 if prob > 0.5 else 0
-
-if __name__ == "__main__":
-    # 加载训练集
-    X_train, y_train = load_data("./data/horse-colic.data")
-
-    # 加载测试集
-    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)
-
-    # 测试单个数据
-    y_pred = predict_logreg(X_test[11], weights)
-    print(f"预测结果: {y_pred}, 实际结果: {int(y_test[11])}")