{
  "fetched_at": "2026-10-20T01:53:49Z",
  "source_url": "https://www.kaggle.com/competitions/beer2019/data",
  "pages": [
    {
      "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!",
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      "content": "<h2>File descriptions</h2>\n<ul>\n<li><strong>beer_train.csv</strong> - the training set</li>\n<li><strong>beer_test.csv</strong> - the test set</li>\n<li><strong>beer_test_sample_submission.csv</strong> - a sample submission file in the correct format</li>\n</ul>\n<h2>Data fields</h2>\n<ul>\n<li><strong>id</strong> - a unique ID for each beer</li>\n<li><strong>name</strong> - the name of the beer</li>\n<li><strong>description</strong> - a description of the beer</li>\n<li><strong>available</strong> - when the beer is available</li>\n<li><strong>isOrganic</strong> - \"Y\" if the beer is organic, \"N\" otherwise</li>\n<li><strong>glass</strong> - the type of glass that the beer is intended to be served in</li>\n<li><strong>abv</strong> - <a href=\"https://en.wikipedia.org/wiki/Alcohol_by_volume\">alcohol by volume</a> of the beer</li>\n<li><strong>originalGravity</strong> - <a href=\"https://en.wikipedia.org/wiki/Gravity_(alcoholic_beverage)\">original gravity</a> of the beer</li>\n<li><strong>srm</strong> - <a href=\"https://en.wikipedia.org/wiki/Standard_Reference_Method\">SRM</a> of the beer</li>\n<li><strong>ibu</strong> - <a href=\"https://en.wikipedia.org/wiki/Beer_measurement\">IBU</a> of the beer</li>\n</ul>",
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    {
      "name": "Description",
      "content": "<p>The International Bittering Units, or IBU, scale is used to quantify the bitterness of a beer. In this competition, you will build a machine learning model to predict the IBU of a beer, given other attributes about the beer, including its color, alcohol content, and other features.</p>",
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      "name": "Evaluation",
      "content": "<p>Submissions will be scored based on root mean-squared error (RMSE) on the test set. If \\(y\\) represents the actual IBU and \\(\\hat y\\) is the predicted IBU, then RMSE is defined as:</p>\n<p>\\[ RMSE = \\sqrt{\\frac{1}{n}\\sum_{i=1}^n (y_i - \\hat y_i)^2}. \\]</p>\n<h2>Submission Format</h2>\n<p>Each beer in the training and test data is given a unique ID. You should submit your predictions for the test data in the following format. (A sample file, <strong>beer_test_sample_submission.csv</strong>, has been provided for you.)</p>\n<pre><span style=\"font-size: 14px; line-height: 1.4em;\">id,ibu<br />6000,38.2<br />6001,13.1<br />6002,40.4<br />6003,22.0<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.<br /></span></pre>",
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