{
  "fetched_at": "2026-10-20T07:38:44Z",
  "source_url": "https://www.kaggle.com/competitions/dsichurnprediction/data",
  "pages": [
    {
      "name": "rules",
      "content": "We will love all participants of this competition to abide by the following rules:\n\n- Let this work be your own effort, avoid cheating or whatever that could make it impossible for you to defend.\n- All Notebooks will be submitted for examination after the end of the competition at  https://tinyurl.com/DataScienceIfeNoteBook\n- please if you have any problem regarding the dataset that you feel admins should be notified of please contact us at  datascienceife@gmail.com",
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      "content": "\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>sampleSubmission.csv</strong> - a sample submission file in the correct format</li>\n\n<h2>Data fields</h2>\n\n<li><strong> Total Spend in Months 1 and 2 of 2017</strong> : The total spend of a customer in the months July & August 2017.</li>\n\n<li><strong>Total SMS Spend</strong> :The total spend on SMS by a customer revenue earned through the SMS service used by the subscriber.</li>\n\n<li><strong> Total Data Spend</strong>: The total amount spend on Data/Internet by a customer revenue earned through the SMS service used by the subscriber.</li>\n\n<li><strong>Total Data Consumption</strong> : The total data consumed by a subscriber in KB over the period under study</li>\n\n<li><strong>Total Unique Calls</strong>: The total count of unique calls made by a subscriber during the period under review</li>\n\n<li><strong>Total Onnet spend</strong>: The total spend of a customer to make on-network calls (on the same network as the subscriber)</li>\n\n<li><strong>Total Offnet spend: Aggregate of Off Net Revenue</strong>: The total spend of a customer to make off-network calls (not the same network as the subscriber)</li>\n\n<li><strong>Customer Tenure in Months</strong>: The time passed since the subscriber started using the services of the network provider and counted in months</li>\n\n<li><strong> Network type subscription in Month 1</strong>: This indicates preferred network subscription of a customer, which may indicate their type of device - 2G or 3G service.</li>\n\n<li><strong>Network type subscription in Month 2</strong>: This indicates preferred network subscription of a customer, which may indicate their type of device - 2G or 3G service in the month after.</li>\n\n<li><strong>Total Call centre complaint calls</strong>: The number of complaints made by the subscribers.</li>\n\n<li><strong>Most Loved Competitor network in in Month 1</strong>: This information certainly have a huge impact on as it gives the information about which other service provider prefer and may likely move to</li>\n\n<li><strong>Most Loved Competitor network in in Month 2</strong>: This information certainly have a huge impact on as it gives the information about which other service provider prefer and may likely move to</li>\n\n<li><strong>Churn Status</strong>: This is an indicator of a customer who leaves the network or not. 1 means the customer has churned and 0 means no churn.</li>\n</ul>\n\n\n",
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    {
      "name": "Description",
      "content": "Churn happens when customers are leaving their current service provider and moving to another one. This is a big business problem because it is more expensive to acquire a new customer than to keep an existing one from leaving. \n\nRead up, fine your model, build incremental statistical thinking and reinforce your Data Science career growth.",
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    {
      "name": "Evaluation",
      "content": "The submission quality metric is accuracy.\n\nAccuracy is calculated as the ratio of correct predictions to the number of total observations.",
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}