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  "source_url": "https://www.kaggle.com/competitions/churn-prediction/data",
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      "name": "data-description",
      "content": "<p>In this competition you are provided with pre-processed data. Your data will have a dimension of N x 8.</p>\r\n<h2>Fields:</h2>\r\n<ol>\r\n<li>Customer_ID: Unique ID for each customer.</li>\r\n<li>Sessions: Connection details for sessions.</li>\r\n<li>Cell_ID: Cell in which device is being used.</li>\r\n<li>District_ID: District where device is being used.</li>\r\n<li>Complaints_U: Complaint feature 1.</li>\r\n<li>Complaints_R: Complaint feature 2.</li>\r\n<li>Complaints_W: Complaint feature 3.</li>\r\n<li>Label</li>\r\n</ol>",
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      "name": "Description",
      "content": "<p>The aim of this competition is to determine weather a customer will churn using usage detail.</p>\r\n<p>Since this is a binary-class problem, you are expected to try linear regression and random forests, and try to minimize the log loss.</p>",
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      "name": "Evaluation",
      "content": "<p>The evaluation metric for this competition is log loss. Log loss calculates overall loss by taking the mean log of probability of correct class. The log of 1 is 0, if the probability of belonging to correct is close to 1, less loss is incurred. As the probability of belonging to correct class approaches 0, more loss is added.</p>\r\n<p>You are expected to reduce your log loss.</p>\r\n<p><img src=\"https://i.stack.imgur.com/NEmt7.png\" alt=\"\" style=\"display: block; margin-left: auto; margin-right: auto;\" height=\"78\" width=\"337\" /></p>\r\n<h2>Submission Format</h2>\r\n<p><strong>For every customer in the dataset</strong>, submission files should contain three columns: <strong>INDEX, PROB_LOYAL and PROB_LEAVE</strong>. Every row should have a probability of staying (PROB_LOYAL) and probability of leaving (PROB_LEAVE).</p>\r\n<p>The file should contain a header and have the following format:</p>\r\n<pre>index,PROB_LOYAL, PROB_LEAVE<br />0, 0.5, 0.5<br /><span style=\"font-size: 14px; line-height: 1.4em;\">1, 0.7, 0.3<br />2, 0.2, 0.8<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">3, 0.35, 0.65<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span></pre>",
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    {
      "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>1/13/2017 5:54 PM UTC</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>1/20/2017 11:59 PM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n",
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