{
  "fetched_at": "2026-10-20T01:13:18Z",
  "source_url": "https://www.kaggle.com/competitions/ccieducationperformance/data",
  "pages": [
    {
      "name": "data-description",
      "content": "`cci_final.csv` is the training data you'll use from Mexico and the Philippines, this is also on `DSS` under `cci_example.csv`.",
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    {
      "name": "Description",
      "content": "This is where you'll submit your data to get a score based on `Categorization Accuracy` for your predictions for the Brazil data. \n\nSubmission files should contain two columns: `Id` and `Predicted`.\n\nWhen you submit your file, **please put your team name in the description**.\n\nThe data file under data is the training file you'll be able to find on `DSS`.\n\nWhen you train your model, you'll use the the satellite imagery and test score data from Mexico and the Philippines to train your models, and then you will generate predictions based on the imagery from Brazil. Your submissions should be a csv with the school ids from Brazil in one column and your predicted class for each school (0 or 1, corresponding to above the mean or below the mean). The `csv` should have 6741 rows.\n\n## Example:\n\n| Id | Predicted  |\n|----|----------|\n| 1234567 | 0|\n| 1234568 | 1|\n\nThe training data is under `cci_final.csv` in the `hmbaier` folder on `DSS`.\n",
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      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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      "hasIsPublished": false,
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  ]
}