{
  "fetched_at": "2026-10-19T17:42:55Z",
  "source_url": "https://www.kaggle.com/competitions/fdacompetition/data",
  "pages": [
    {
      "name": "data-description",
      "content": "This third assignment picks up from your second assignment, where you explored the dataset. \nNow you will build different classifiers to predict if a hotel booking is canceled or not.\n\nThe classification goal is to predict if a booking gets canceled or not.\n\n## Files\n\n*   **Assignment3-SatisfactionDataset.csv** - the training set\n*   **Assignment3-UnknownDatasetcsv** - the test set\n*   **Assignment3-sample_submission.csv** - a sample submission file in the correct format\n\n\n",
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    {
      "name": "Description",
      "content": "## 32130 Fundamentals in Data Analytics Kaggle Competition\n\nThis third assignment picks up from your second assignment, where you explored the dataset. \nNow you will build different classifiers to predict if an airline passenger is satisfied or not. \n\nThe classification goal is to predict if a passenger is satisfied or not. ",
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    {
      "name": "Evaluation",
      "content": "The evaluation pages describes how submissions will be scored and how you should format your submission.\n\n## Submission Format\nFor each data point, you need to give the identifier (Id) together with the class value you predicted for \"satisfied\". The \"Id\" is an increasing number from 1 until the end (indicated by `N`) of the `Assignment3-UnknownDataset.csv` (Canvas) or `test.csv` (from this Kaggle competition).\n\nThe file should contain a header including the `Id` and the prediction for `satisfied` in the following format: \n\n```\nId, is_canceled\n1, 1\n2, 0\n3, 0\n4, 1\n  .\n  .\n  .\nN, 0\n```",
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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 - Apply yourself!\n - Have fun!\n- Test how you rank to other submissions!",
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