{
  "id": 327513,
  "title": "Does anyone have any ideas about this competition？",
  "url": "/competitions/amex-default-prediction/discussion/327513",
  "author_name": "SgangX",
  "post_date": "2022-05-27T14:52:59.750000",
  "votes": 3,
  "comment_count": 6,
  "views": 0,
  "content": "<p>I very much like to know some ideas about this competition such as model selection, dealing with missing feature and how to do feature engineering~~</p>",
  "messages": [
    {
      "id": 1803513,
      "postDate": "2022-05-27T22:21:17.983Z",
      "content": "<p>Hello, <a href=\"https://www.kaggle.com/shanggangli\" target=\"_blank\">@shanggangli</a>. I'm just getting started, but there are plenty of ideas in some of the discussions. I will recommend checking similar competitions.</p>",
      "rawMarkdown": "Hello, @shanggangli. I'm just getting started, but there are plenty of ideas in some of the discussions. I will recommend checking similar competitions.",
      "votes": 1,
      "replies": [
        {
          "id": 1807394,
          "postDate": "2022-06-01T01:18:14.453Z",
          "content": "<p>Thank you for your advice~~~👍</p>",
          "rawMarkdown": "Thank you for your advice~~~👍"
        }
      ]
    },
    {
      "id": 1803194,
      "postDate": "2022-05-27T14:52:59.750Z",
      "content": "<p>I very much like to know some ideas about this competition such as model selection, dealing with missing feature and how to do feature engineering~~</p>",
      "rawMarkdown": "I very much like to know some ideas about this competition such as model selection, dealing with missing feature and how to do feature engineering~~",
      "votes": 2
    },
    {
      "id": 1803890,
      "postDate": "2022-05-28T09:27:51.130Z",
      "content": "<p>DO not use all the data, IMO you can get pretty decent results with a fraction of the data</p>",
      "rawMarkdown": "DO not use all the data, IMO you can get pretty decent results with a fraction of the data\n",
      "replies": [
        {
          "id": 1807392,
          "postDate": "2022-06-01T01:17:17.217Z",
          "content": "<p>How robust is this?</p>",
          "rawMarkdown": "How robust is this?"
        }
      ]
    },
    {
      "id": 1807051,
      "postDate": "2022-05-31T17:02:18.197Z",
      "rawMarkdown": "",
      "votes": 1,
      "isDeleted": true,
      "replies": [
        {
          "id": 1807395,
          "postDate": "2022-06-01T01:19:27.153Z",
          "content": "<p>👍Thank you for your advice and l will try my best to do it.</p>",
          "rawMarkdown": "👍Thank you for your advice and l will try my best to do it."
        }
      ]
    }
  ],
  "comments": [
    {
      "id": 1803513,
      "author_name": "C4rl05/V",
      "author_url": "",
      "post_date": "2022-05-27T22:21:17.983000",
      "content": "<p>Hello, <a href=\"https://www.kaggle.com/shanggangli\" target=\"_blank\">@shanggangli</a>. I'm just getting started, but there are plenty of ideas in some of the discussions. I will recommend checking similar competitions.</p>",
      "votes": 1,
      "replies": [
        {
          "id": 1807394,
          "author_name": "SgangX",
          "author_url": "",
          "post_date": "2022-06-01T01:18:14.453000",
          "content": "<p>Thank you for your advice~~~👍</p>",
          "votes": 0,
          "replies": []
        }
      ]
    },
    {
      "id": 1803890,
      "author_name": "wuuthraad",
      "author_url": "",
      "post_date": "2022-05-28T09:27:51.130000",
      "content": "<p>DO not use all the data, IMO you can get pretty decent results with a fraction of the data</p>",
      "votes": 0,
      "replies": [
        {
          "id": 1807392,
          "author_name": "SgangX",
          "author_url": "",
          "post_date": "2022-06-01T01:17:17.217000",
          "content": "<p>How robust is this?</p>",
          "votes": 0,
          "replies": []
        }
      ]
    },
    {
      "id": 1807051,
      "author_name": "",
      "author_url": "",
      "post_date": "2022-05-31T17:02:18.197000",
      "content": "",
      "votes": 1,
      "replies": [
        {
          "id": 1807395,
          "author_name": "SgangX",
          "author_url": "",
          "post_date": "2022-06-01T01:19:27.153000",
          "content": "<p>👍Thank you for your advice and l will try my best to do it.</p>",
          "votes": 0,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "1803513": "Hello, @shanggangli. I'm just getting started, but there are plenty of ideas in some of the discussions. I will recommend checking similar competitions.",
    "1803194": "I very much like to know some ideas about this competition such as model selection, dealing with missing feature and how to do feature engineering~~",
    "1803890": "DO not use all the data, IMO you can get pretty decent results with a fraction of the data\n",
    "1807051": ""
  }
}