{
  "fetched_at": "2026-10-20T09:19:59Z",
  "source_url": "https://www.kaggle.com/competitions/gvu-spring-2024-project-2/data",
  "pages": [
    {
      "name": "data-description",
      "content": "## Files\n\n*   **train.csv** - the training set\n*   **test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n\n## Columns\n\n* Cement (component 1) -- quantitative -- kg in a m3 mixture -- Input Variable\n* Blast Furnace Slag (component 2) -- quantitative -- kg in a m3 mixture -- Input Variable\n* Fly Ash (component 3) -- quantitative -- kg in a m3 mixture -- Input Variable\n* Water (component 4) -- quantitative -- kg in a m3 mixture -- Input Variable\n* Superplasticizer (component 5) -- quantitative -- kg in a m3 mixture -- Input Variable\n* Coarse Aggregate (component 6) -- quantitative -- kg in a m3 mixture -- Input Variable\n* Fine Aggregate (component 7) -- quantitative -- kg in a m3 mixture -- Input Variable\n* Age -- quantitative -- Day (1~365) -- Input Variable\n* Concrete compressive strength -- quantitative -- MPa -- Target Variable \n",
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    {
      "name": "Description",
      "content": "Submissions are evaluated on mean absolute error.\n\n## Submission File\nFor each ID in the test set, you must predict a number for the Concrete compressive strength variable. The file should contain a header and have the following format:\n\n    id,Concrete compressive strength(MPa, megapascals)\n    1,35\n    2,35\n    3,35\n    etc.",
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    {
      "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 - Try your best to make improvements day after day \n - Apply yourself!\n - Have fun!",
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    {
      "name": "abstract",
      "content": "Welcome to the second project of DATA-448 in Spring-2024. In this project, students will build regression models to predict a numeric variable.",
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}