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  "fetched_at": "2026-10-19T19:11:57Z",
  "source_url": "https://www.kaggle.com/competitions/fall-2018-stat-441841-data-challenge-2/data",
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    {
      "name": "rules",
      "content": "\n    <!-- Begin Base Rules -->\t\n    <h3>One account per participant</h3>\n    <p>You cannot submit from multiple accounts.</p>\n    <h3>No private sharing outside teams</h3>\n    <p>Privately sharing code or data outside of teams is not permitted.\n        It's okay to share code if made available to all participants on the forums.</p>\n    <h3>Team Mergers</h3>\n    <p>Team mergers are not allowed in this competition.</p>\n\n    <h3>Team Limits</h3>\n    <p>One account</p>\n    <h3>Submission Limits</h3>\n    <p>You may submit a maximum of 3 entries per day.</p>\n    <p>You may select up to 2 final submissions for judging.</p>\n ",
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      "content": " <p>There are 12 measures, but 54 columns of data\n\t\t\t\t(10 quantitative variables, 4 binary\n\t\t\t\twilderness areas and 40 binary\n\t\t\t\tsoil type variables)\n   You should develop a classification model based on the training set and use that model to make predictions for the test set. Then organize your predictions in the same format with the\n   sample_submission file and submit.</p>\n\n<p>Be aware that each account can only make 3 submissions per day so start early is an advantage. The score you see on public leader board is based on ~30% percent of test set so it might be slightly different from the final result.</p>\n<h2>File descriptions</h2>\n<ul>\n<li><strong>train.csv</strong> - the training set</li>\n<li><strong>test.csv</strong> - the test set</li>\n<li><strong>sample_submission.csv</strong> - a sample submission file in the correct format</li>\n\n<h2>Forest CoverType</h2>\n\n - 1\n - 2\n - 3\n - 4\n - 5\n - 6\n - 7\n",
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      "name": "Description",
      "content": "<p>This is the second data challenge for STAT 441/841 and CM 763, fall 2018. The data set is borrowed from the Forest CoverType dataset. Please do not download the test set from the original page and do not use any test set information when developing your model. Your code will be checked to see if it matches your submitted result.</p>\n\n<p>Please use your UWaterloo username as your team name, or the marker might not be able to find your results.</p>\n\n\n[The Forest CoverType dataset][1]\n\n\n  [1]: https://archive.ics.uci.edu/ml/datasets/Covertype",
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      "name": "Evaluation",
      "content": "<p>Submissions are evaluated on overall accuracy between the predicted label and the ground truth label.</p>\n\n<h2>Submission Format</h2>\n<p><strong>For each \"ids\" in the test set, you must predict a probability for the \"Forest CoverType\" variable. The file should contain a header and have the following format:</p>\n\n<pre>ids,Forest CoverType<br />1,2<br /><span style=\"font-size: 14px; line-height: 1.4em;\">2,7<br />3,6<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">4,5<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span></pre>",
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