{
  "id": 40476,
  "title": "Log-Loss Evaluation Metric",
  "url": "/competitions/kkbox-churn-prediction-challenge/discussion/40476",
  "author_name": "Djoko Soehartono",
  "post_date": "2017-10-03T08:34:55.902000",
  "votes": 3,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Is the evaluation metric is actually Log-Loss? One way to check this is to set blindly is_churn = 0.5 for all msno in sample_submission_zero.csv for data submission. According to Log-Loss function, this will result to log(2) =  0.6931472 regardless the actual binary target yi values, either 0 or 1.</p>\n\n<p>I tried to submit this sample_submission_zero.csv with is_churn value is set at 0.5 for all rows and expecting to get a score of 0.6931472. I got a score of 1.70064 instead.</p>\n\n<p>Did I interpret Log-Loss function correctly or did I miss anything here?</p>",
  "messages": [
    {
      "id": 226875,
      "postDate": "2017-10-03T08:34:55.903Z",
      "content": "<p>Is the evaluation metric is actually Log-Loss? One way to check this is to set blindly is_churn = 0.5 for all msno in sample_submission_zero.csv for data submission. According to Log-Loss function, this will result to log(2) =  0.6931472 regardless the actual binary target yi values, either 0 or 1.</p>\n\n<p>I tried to submit this sample_submission_zero.csv with is_churn value is set at 0.5 for all rows and expecting to get a score of 0.6931472. I got a score of 1.70064 instead.</p>\n\n<p>Did I interpret Log-Loss function correctly or did I miss anything here?</p>",
      "rawMarkdown": "Is the evaluation metric is actually Log-Loss? One way to check this is to set blindly is_churn = 0.5 for all msno in sample_submission_zero.csv for data submission. According to Log-Loss function, this will result to log(2) =  0.6931472 regardless the actual binary target yi values, either 0 or 1.\n\nI tried to submit this sample_submission_zero.csv with is_churn value is set at 0.5 for all rows and expecting to get a score of 0.6931472. I got a score of 1.70064 instead.\n\nDid I interpret Log-Loss function correctly or did I miss anything here?",
      "votes": 3
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "226875": "Is the evaluation metric is actually Log-Loss? One way to check this is to set blindly is_churn = 0.5 for all msno in sample_submission_zero.csv for data submission. According to Log-Loss function, this will result to log(2) =  0.6931472 regardless the actual binary target yi values, either 0 or 1.\n\nI tried to submit this sample_submission_zero.csv with is_churn value is set at 0.5 for all rows and expecting to get a score of 0.6931472. I got a score of 1.70064 instead.\n\nDid I interpret Log-Loss function correctly or did I miss anything here?"
  }
}