{
  "fetched_at": "2026-10-24T10:06:13Z",
  "source_url": "https://www.kaggle.com/competitions/analyticssummit19/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!",
      "isPublished": false,
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    {
      "name": "data-description",
      "content": "<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>sampleSubmission.csv</strong> - a benchmark submission from a random forest model</li>\n</ul>\n<h2>Data fields</h2>\n<p>\nSee `?AmesHousing::ames_raw` for details on all data fields\n</p>",
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    {
      "name": "Description",
      "content": "<p>Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.</p>\n\n<p>\nWith 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.</p>\n\n<h2>Practice Skills</h2>\n\n<p>\nCreative feature engineering \nAdvanced regression techniques like random forest and gradient boosting</p>\n\n<h2>Acknowledgments</h2>\n\n<p>\nThe Ames Housing dataset was compiled by Dean De Cock for use in data science education. It's an incredible alternative for data scientists looking for a modernized and expanded version of the often cited Boston Housing dataset. \n</p>\n",
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    },
    {
      "name": "Evaluation",
      "content": "<p>It is your job to predict the sales price for each house. For each Id in the test set, you must predict the value of the SalePrice variable. </p>\n<hr>\n<p>Submissions are evaluated on Root-Mean-Squared-Error (RMSE) between the predicted value and the observed sales price. </p>\n<h2>Submission Format</h2>\n<p>The file should contain a header and have the following format:</p>\n<pre>Id, Sale_Price</pre>",
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}