Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
官方直播
Python-test_278877
提交
f7f1b904
P
Python-test_278877
项目概览
官方直播
/
Python-test_278877
与 Fork 源项目一致
Fork自
唯有杜康TM / Python获取主机系统环境信息
通知
1
Star
0
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
DevOps
流水线
流水线任务
计划
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Python-test_278877
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
DevOps
DevOps
流水线
流水线任务
计划
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
流水线任务
提交
Issue看板
提交
f7f1b904
编写于
5月 11, 2023
作者:
6
622ee496dfef6c4fdb84cccd
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Thu May 11 07:28:00 UTC 2023 inscode
上级
82e16a2c
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
50 addition
and
4 deletion
+50
-4
test.ipynb
test.ipynb
+50
-4
未找到文件。
test.ipynb
浏览文件 @
f7f1b904
...
...
@@ -14,10 +14,56 @@
}
],
"source": [
"import datetime\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"today = datetime.date.today()\n",
"print(\"今天的日期是: \", today)\n"
"\n",
"def sigmoid(z):\n",
" return 1 / (1 + np.exp(-z))\n",
"\n",
"def costFunction(theta, X, y):\n",
" m = len(y)\n",
" J = 0\n",
" grad = np.zeros(theta.shape)\n",
" \n",
" h = sigmoid(np.dot(X, theta))\n",
" J = (-1/m) * np.sum(y*np.log(h) + (1-y)*np.log(1-h))\n",
" grad = (1/m) * np.dot(X.T, (h-y))\n",
" \n",
" return J, grad\n",
"\n",
"def gradientDescent(X, y, theta, alpha, num_iters):\n",
" m = len(y)\n",
" J_history = np.zeros(num_iters)\n",
" \n",
" for i in range(num_iters):\n",
" J_history[i], grad = costFunction(theta, X, y)\n",
" theta = theta - alpha*grad\n",
" \n",
" return theta, J_history\n",
"\n",
"# 生成样本数据\n",
"np.random.seed(0)\n",
"X = np.random.randn(100, 2)\n",
"ones = np.ones((100, 1))\n",
"X = np.hstack((ones, X))\n",
"y = np.random.randint(0, 2, size=(100,1))\n",
"\n",
"# 初始化theta\n",
"initial_theta = np.zeros((X.shape[1], 1))\n",
"\n",
"# 梯度下降\n",
"alpha = 0.1\n",
"num_iters = 1000\n",
"theta, J_history = gradientDescent(X, y, initial_theta, alpha, num_iters)\n",
"\n",
"# 绘制决策边界\n",
"x1 = np.arange(-3, 3, 0.1)\n",
"x2 = -(theta[0]+theta[1]*x1)/theta[2]\n",
"plt.plot(x1, x2, label='Decision Boundary')\n",
"plt.scatter(X[:, 1], X[:, 2], c=y.flatten())\n",
"plt.legend()\n",
"plt.show()\n"
]
},
{
...
...
@@ -114,7 +160,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.5"
"version": "3.9.5
(default, Nov 23 2021, 15:27:38) \n[GCC 9.3.0]
"
},
"orig_nbformat": 4,
"vscode": {
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录