{
  "fetched_at": "2026-10-20T03:22:49Z",
  "source_url": "https://www.kaggle.com/competitions/dsn-telecom-customer-churn/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,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "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</ul>\n<h2>Data fields</h2>\n<ul>\n<li>Customers who left within the last month – the column is called Churn</li>\n<li>Services that each customer has signed up for – phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming TV and movies</li>\n<li>Customer account information – how long they’ve been a customer, contract, payment method, paperless billing, monthly charges, and total charges</li>\n<li>Demographic info about customers – gender, age range, and if they have partners and dependents</li>\n</ul>\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
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    },
    {
      "name": "Description",
      "content": "<p>Mr Ayo is the owner of XYZ Telecommunication industry, it was established in the year 2015. Recently, Mr Ayo notices that most of their customers are leaving them for their other competitor. various marketing strategy has failed to yield the desiral results</p>\n<p>This is where you come in. Mr Ayo has empoly  you to use your machine learning skills to study the important features among available features that can be used to determine if a customer will stay or leave so as to improve their marketing strategy</p>\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Evaluation",
      "content": "<p>The evaluation pages describes how submissions will be scored and how students should format their submissions. You don't need a sub-title at the top (the page title appears above). For an example of a high quality evaluation page, see the 2013 KDD Cup page, which we have copied here:</p>\n<hr />\n<p>The evaluation metric for this competition is <a href=\"https://www.kaggle.com/wiki/MeanFScore\"> Mean F1-Score</a>. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:</p>\n<p>\\[ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} \\]</p>\n<p>The F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.</p>\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}