{
  "id": 44203,
  "title": "submission question - Are we trying to predict May or April?",
  "url": "/competitions/kkbox-churn-prediction-challenge/discussion/44203",
  "author_name": "Vishnu Vardhan",
  "post_date": "2017-11-25T06:46:33.008000",
  "votes": 0,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Hi,</p>\n\n<p>Are we trying to predict churn for the month of 'May', using data for customer expiring(?) in April (+ 30 days for a chance to renew), </p>\n\n<p>OR</p>\n\n<p>Are we trying to predict churn for month of 'April, using data for customers expiring(?) expiring in March (+30 days to renew).</p>\n\n<p>I am confused because the Nov 6 update, seems identical to the guidelines earlier. </p>\n\n<p>Guidelines state state the below:</p>\n\n<p>The train and the test data are selected from users whose <strong>membership expire within a certain month</strong>. The train data consists of users whose subscription expires within the month of February 2017 . This means we are looking at user churn or renewal roughly in the month of March 2017 for train set, <strong>and the user churn or renewal roughly in the month of April 2017.</strong> </p>\n\n<p>UPDATE: As of November 6, 2017, we have refreshed the test data to predict user churn in the <strong>month of April, 2017.</strong></p>",
  "messages": [
    {
      "id": 248185,
      "postDate": "2017-11-25T06:46:33.010Z",
      "content": "<p>Hi,</p>\n\n<p>Are we trying to predict churn for the month of 'May', using data for customer expiring(?) in April (+ 30 days for a chance to renew), </p>\n\n<p>OR</p>\n\n<p>Are we trying to predict churn for month of 'April, using data for customers expiring(?) expiring in March (+30 days to renew).</p>\n\n<p>I am confused because the Nov 6 update, seems identical to the guidelines earlier. </p>\n\n<p>Guidelines state state the below:</p>\n\n<p>The train and the test data are selected from users whose <strong>membership expire within a certain month</strong>. The train data consists of users whose subscription expires within the month of February 2017 . This means we are looking at user churn or renewal roughly in the month of March 2017 for train set, <strong>and the user churn or renewal roughly in the month of April 2017.</strong> </p>\n\n<p>UPDATE: As of November 6, 2017, we have refreshed the test data to predict user churn in the <strong>month of April, 2017.</strong></p>",
      "rawMarkdown": "Hi,\n\nAre we trying to predict churn for the month of 'May', using data for customer expiring(?) in April (+ 30 days for a chance to renew), \n\nOR\n\nAre we trying to predict churn for month of 'April, using data for customers expiring(?) expiring in March (+30 days to renew).\n\nI am confused because the Nov 6 update, seems identical to the guidelines earlier. \n\nGuidelines state state the below:\n\nThe train and the test data are selected from users whose **membership expire within a certain month**. The train data consists of users whose subscription expires within the month of February 2017 "
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "248185": "Hi,\n\nAre we trying to predict churn for the month of 'May', using data for customer expiring(?) in April (+ 30 days for a chance to renew), \n\nOR\n\nAre we trying to predict churn for month of 'April, using data for customers expiring(?) expiring in March (+30 days to renew).\n\nI am confused because the Nov 6 update, seems identical to the guidelines earlier. \n\nGuidelines state state the below:\n\nThe train and the test data are selected from users whose **membership expire within a certain month**. The train data consists of users whose subscription expires within the month of February 2017 "
  }
}