{
  "fetched_at": "2026-10-20T03:30:57Z",
  "source_url": "https://www.kaggle.com/competitions/generalization-competition/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,
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      "postTitle": "",
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    {
      "name": "data-description",
      "content": "Given the small training data, can you generalize well on the large testing set?\n\nThe goal here is to implement a learning algorithm that can generalize well on unseen data. You will be given 100 samples regarding sales data. The testing set consist of more than 19,000 samples.\n\nColumns Available:\n\n- Cost = Total Cost for Production.\n- Ad Responses = Number of responses received per location regarding an advertisment.\n- Location Participation = Rate of location participation to a certain corporate objective.",
      "isPublished": false,
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      "postTitle": "",
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    },
    {
      "name": "Description",
      "content": "The goal here is to implement a learning algorithm that can generalize well on unseen data. You will be given 100 samples regarding sales data. The testing set consist of more than 19,000 samples.\n\nColumns Available:\n\n- Cost = Total Cost for Production.\n- Ad Responses = Number of responses received per location regarding an advertisment.\n- Location Participation = Rate of location participation to a certain corporate objective.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Evaluation",
      "content": "The evaluation metric is the Root Mean Squared Error",
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      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
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  ]
}