{
  "id": 175860,
  "title": "Relevant noise to add in validation set to mimic the test set",
  "url": "/competitions/birdsong-recognition/discussion/175860",
  "author_name": "Saransh Agarwal",
  "post_date": "2020-08-19T16:51:01.009000",
  "votes": 0,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Hi!</p>\n<p>I just joined the competition, from what I have looked there is a considerable difference in the train and test data, with the test data having some noise in it.<br>\nAre there any augmentations that could somewhat add a noise to the train data to make it more closer to the test set?</p>\n<p>Thanks!</p>",
  "messages": [
    {
      "id": 977702,
      "postDate": "2020-08-19T16:51:01.010Z",
      "content": "<p>Hi!</p>\n<p>I just joined the competition, from what I have looked there is a considerable difference in the train and test data, with the test data having some noise in it.<br>\nAre there any augmentations that could somewhat add a noise to the train data to make it more closer to the test set?</p>\n<p>Thanks!</p>",
      "rawMarkdown": "Hi!\n\nI just joined the competition, from what I have looked there is a considerable difference in the train and test data, with the test data having some noise in it.\nAre there any augmentations that could somewhat add a noise to the train data to make it more closer to the test set?\n\nThanks!"
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "977702": "Hi!\n\nI just joined the competition, from what I have looked there is a considerable difference in the train and test data, with the test data having some noise in it.\nAre there any augmentations that could somewhat add a noise to the train data to make it more closer to the test set?\n\nThanks!"
  }
}