{
  "fetched_at": "2026-10-22T07:28:46Z",
  "source_url": "https://www.kaggle.com/competitions/cm256-1-uiuc/data",
  "pages": [
    {
      "name": "rules",
      "content": "\r\n\t<!-- Begin Base Rules -->\r\n    <h3>One account per participant</h3>\r\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\r\n    <h3>No private sharing outside teams</h3>\r\n    <p>\r\n        Privately sharing code or data outside of teams is not permitted.\r\n        It's okay to share code if made available to all participants on the forums.\r\n    </p>\r\n    <h3>Team Mergers</h3>\r\n    <p>Team mergers are not allowed in this competition.</p>\r\n\r\n    <h3>Team Limits</h3>\r\n    <p>There is no maximum team size.</p>\r\n    <h3>Submission Limits</h3>\r\n    <p>You may submit a maximum of 2 entries per day.</p>\r\n    <p>You may select up to 2 final submissions for judging.</p>\r\n    <h3>Competition Timeline</h3>\r\n    <p>Start Date: <strong>TBA</strong></p>\r\n    <p>Merger Deadline: <strong>None</strong></p>\r\n    <p>Entry Deadline: <strong>None</strong></p>\r\n    <p>End Date: <strong>2/1/2014 12:00 AM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n<p>The rules page is a bit special: it will auto-update the text based on the parameters of the competition. The rules you need to add here are any additional rules relating to dataset usage. You may also put grading information here.</p>",
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      "name": "data-description",
      "content": "\n<h2>Description of the Data</h2>\n\nThe goal of this competition is to predict the value of R(x) for a number of values of distance to the highway. The csv file \"train\" contains data on the distance to the highway and average revenue for 30 restaurants$$\\{(x_i,R(x_i))\\}_{i=1}^{30},$$ You can use these data to create predictions of average revenue for the remaining 10 restaurants. For these 10 restaurants you only observe their distances to the highway in the csv file \"test.\" You can find an example of how your submission must look like in the csv file \"sample_submission.\"\n\n</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> - an example of a submission file in the correct format</li>\n\n\n<h2>Submission File:</h2>\n\n\nThe submission file <strong>must be in csv format</strong>. For every distance to the highway of the 10 restaurants, your submission files should contain two columns:  distance to the highway (x) and average revenue prediction (R). The file should contain a header and have the following format:\n\n<br>  &nbsp;&nbsp;x &nbsp;  ,&nbsp;&nbsp;  R\n<br> 1.047579, 34.43375\n<br> 1.926801, 36.83077\n<br> etc.\n<br> \n<br>A correct submission must be a csv file with one row of headers and 10 rows of numerical data, as displayed above. To ensure that you are uploading your predictions in the correct format, we recommend that you upload your predictions by editing the sample submission file. There is a limit of 10 submissions per day.\n",
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      "name": "Description",
      "content": "\n<h2>Description of the Competition</h2>\n\n<p>\nA large restaurant chain owns restaurants located along major highways. The average revenue of a restaurant located at distance x from the highway is R(x). For simplicity, the variable distance to the highway is normalized to be in the interval [1,2]. The function R(x) is unknown. The goal of this competition is to predict the value of R(x) for several values of distances to the highway. Currently, the restaurant chain is located at 40 different locations. You will have access to $$\\{(x_i,R(x_i))\\}_{i=1}^{30},$$\ni.e., the distance to the highway and average revenue for 30 of these restaurants. Using these data, you must submit a prediction of average revenue for the remaining 10 restaurants, using their distances to the highway.\n</p>\n\n<p>You will find the necessary datasets in the Data tab. You can send up to 10 different submission each day until the end of the competition. The deadline of the competition is <strong>Sunday April 15th at 23:59:59</strong>.</p>\n",
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      "name": "Evaluation",
      "content": "\n<h2>Evaluation</h2>\n\nWe will compare the actual revenue and the revenue predictions for each value $$(x_{j})_{j=31}^{40}.$$ The score will be calculated according to the Root Mean Square Deviation:\n\n$$\\operatorname{RMSD}=\\sqrt{\\frac{\\sum_{j=31}^{40} (\\hat{R}(x_{j}) - R(x_{j}))^2}{10}},$$\nwhich is a measure of the distance between your predictions and the actual values R(x).\nThe deadline of the competition is Sunday April 15th at 23:59:59.\n",
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