{
  "fetched_at": "2026-10-20T01:20:26Z",
  "source_url": "https://www.kaggle.com/competitions/2024-4-big-data-analytics-certification-kr/data",
  "pages": [
    {
      "name": "Evaluation",
      "content": "## Evaluation\n\nSubmissions will be evaluated using [Mean Absolute Error (MAE)](https://en.wikipedia.org/wiki/Mean_absolute_error),\n\n![MAE](https://raw.githubusercontent.com/visipedia/iwildcam_comp/master/assets/MAE.png)\n\nwhere each `x_i` represents the predicted target, `y_i` represents the ground truth, and `n` is the number of rows in the test set.\n\n## Submission File\nFor each `id` in the test set, you must predict the target `Age`. The file should contain a header and have the following format:\n\n    id,yield\n    74051,10\n    74051,3\n    74051,11\n    etc.",
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      "hasIsPublished": false,
      "postTitle": "",
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      "hasMimeType": false
    },
    {
      "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!\n\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    {
      "name": "data-description",
      "content": "## Files\n\n*   **train.csv** - the training dataset; `Age` is the target\n*   **test.csv** - the test dataset; your objective is to predict the probability of `Age` (the ground truth is `int` but you can predict `int` or `float`)\n*   **sample_submission.csv** - a sample submission file in the correct format",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
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    },
    {
      "name": "abstract",
      "content": "**Your Goal:** For this Episode of the Series, your task is to use regression to predict the age of crabs given physical attributes. Good luck!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
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    }
  ]
}