{
  "id": 216323,
  "title": "Train.csv  Table",
  "url": "/competitions/ranzcr-clip-catheter-line-classification/discussion/216323",
  "author_name": "",
  "post_date": "2021-02-02T12:13:07.843038700Z",
  "votes": 3,
  "comment_count": 1,
  "views": 0,
  "content": "<p>In Train.csv what does 0 and 1 mean in the Table ?</p>",
  "messages": [
    {
      "id": "1182323",
      "postDate": "02/02/2021 12:13:07",
      "content": "<p>In Train.csv what does 0 and 1 mean in the Table ?</p>",
      "rawMarkdown": "In Train.csv what does 0 and 1 mean in the Table ?",
      "votes": null
    },
    {
      "id": "1187186",
      "postDate": "02/05/2021 09:15:47",
      "content": "<p>If you mean in the columns like \"ETT - Abnormal\", \"ETT - Borderline\" and so on, then it means whether that particular interpretation of the x-ray is present (1) or absent (0). For each of the images, each of these columns is something you should train a model to predict (i.e. it's a multi-label binary prediction task = for each image you need to predict several things that are all 1:yes/present vs. 0: no/absent).</p>",
      "rawMarkdown": "If you mean in the columns like \"ETT - Abnormal\", \"ETT - Borderline\" and so on, then it means whether that particular interpretation of the x-ray is present (1) or absent (0). For each of the images, each of these columns is something you should train a model to predict (i.e. it's a multi-label binary prediction task = for each image you need to predict several things that are all 1:yes/present vs. 0: no/absent).",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1187186,
      "author_name": "bjoernholzhauer",
      "author_url": "",
      "post_date": "02/05/2021 09:15:47",
      "content": "<p>If you mean in the columns like \"ETT - Abnormal\", \"ETT - Borderline\" and so on, then it means whether that particular interpretation of the x-ray is present (1) or absent (0). For each of the images, each of these columns is something you should train a model to predict (i.e. it's a multi-label binary prediction task = for each image you need to predict several things that are all 1:yes/present vs. 0: no/absent).</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1182323": "In Train.csv what does 0 and 1 mean in the Table ?",
    "1187186": "If you mean in the columns like \"ETT - Abnormal\", \"ETT - Borderline\" and so on, then it means whether that particular interpretation of the x-ray is present (1) or absent (0). For each of the images, each of these columns is something you should train a model to predict (i.e. it's a multi-label binary prediction task = for each image you need to predict several things that are all 1:yes/present vs. 0: no/absent)."
  },
  "source": "meta"
}