{
  "fetched_at": "2026-10-19T19:17:19Z",
  "source_url": "https://www.kaggle.com/competitions/cquai002/data",
  "pages": [
    {
      "name": "rules",
      "content": "\r\n\t<!-- Begin Base Rules -->\r\n    <h3>One account per participant</h3>\r\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\r\n    <h3>No private sharing outside teams</h3>\r\n    <p>\r\n        Privately sharing code or data outside of teams is not permitted.\r\n        It's okay to share code if made available to all participants on the forums.\r\n    </p>\r\n    <h3>Team Mergers</h3>\r\n    <p>Team mergers are not allowed in this competition.</p>\r\n\r\n    <h3>Team Limits</h3>\r\n    <p>There is no maximum team size.</p>\r\n    <h3>Submission Limits</h3>\r\n    <p>You may submit a maximum of 2 entries per day.</p>\r\n    <p>You may select up to 2 final submissions for judging.</p>\r\n    <h3>Competition Timeline</h3>\r\n    <p>Start Date: <strong>TBA</strong></p>\r\n    <p>Merger Deadline: <strong>None</strong></p>\r\n    <p>Entry Deadline: <strong>None</strong></p>\r\n    <p>End Date: <strong>2/1/2014 12:00 AM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n<p>The rules page is a bit special: it will auto-update the text based on the parameters of the competition. The rules you need to add here are any additional rules relating to dataset usage. You may also put grading information here.</p>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "data-description",
      "content": "<p>数据描述</h2>\n<ul>\n<li><strong>提交示例.csv</strong> -你要提交的数据格式</li>\n<li><strong>训练数据.csv</strong> -用来训练模型的数据</li>\n<li><strong>测试数据.csv</strong> - 用来得到答案的数据</li>\n</ul>\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Description",
      "content": "\n\n\n<p>欢迎大家参与cquai 的第一个训练赛。\n</p>\n\n<h2>该比赛做什么</h2>\n这个比赛的任务是\n预测TED的观看人数\n<h2>数据说明</h2>\n每一个TED的演讲会对应一个id，我们可以得到他的views，即观看人数的数据。同时还有很多相关的自变量。\n我们要做的就是利用训练数据建一个模型预测测试数据的观看人数。\n<h2>如何参加比赛</h2>\n1. 下载训练数据训练一下模型\n2. 用测试数据得到对应id的 views数量\n3. 按照提交示例的样式提交\n4. 查看排名\n<h2>我是新手怎么办呢</h2>\n1.大家有问题请在qq群或者论坛留言发帖，一起讨论。\n2. 关注论坛有一个简单的教程指导大家\n<p>数据来源于 kaggle</p>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Evaluation",
      "content": "<p>评价方法</p>\n使用均方根RMSE评价模型性能。",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}