From 780e2892797d16a18e0dc77fa6e18a9fed4fdf19 Mon Sep 17 00:00:00 2001 From: llll <2992513220@qq.com> Date: Thu, 31 Oct 2024 23:22:54 +0800 Subject: [PATCH] =?UTF-8?q?=E6=9B=B4=E6=96=B0=20function.py?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- function.py | 18 ++++++++++++++++-- 1 file changed, 16 insertions(+), 2 deletions(-) diff --git a/function.py b/function.py index bc959e9..a352d84 100644 --- a/function.py +++ b/function.py @@ -1,6 +1,5 @@ # function.py import numpy as np -from scipy.optimize import minimize """ 实验说明: - 自行编写实现数据加载与预测病马死亡的对率回归算法。 @@ -95,4 +94,19 @@ 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 \ No newline at end of file + return 1 if prob > 0.5 else 0 + +# 移除以下测试代码,仅在本地测试时使用 +# 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])}") \ No newline at end of file