{
  "fetched_at": "2026-10-19T14:35:47Z",
  "source_url": "https://www.kaggle.com/competitions/20-ades/data",
  "pages": [
    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "data-description",
      "content": "**Two files are provided:**\n- dev.csv: data to develop the models\n- compete.csv: data to generate predictions for submission in kaggle\n\n**Data dictionary**\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Description",
      "content": "The intrusion detector learning task is to build a predictive model (i.e. a classifier) capable of distinguishing between \"bad\" connections, called intrusions or attacks, and \"good\" normal connections.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Evaluation",
      "content": "<p>The evaluation metric for this competition is AUC.</p>\n<h2>Submission Format</h2>\n<p>Submission files should contain two columns: Id and class. Class can be one of {0,1} but it can also be a score in the domain [0,1].</p>\n<p>The file should contain a header and have the following format:</p>\n<pre>Id,class<br />1,1<br /><span style=\"font-size: 14px; line-height: 1.4em;\">8,8<br />9,9 10<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">10,10 9<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span></pre>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}