{
  "id": 498623,
  "title": "LightGBM best parameter trained on Local PC",
  "url": "/competitions/home-credit-credit-risk-model-stability/discussion/498623",
  "author_name": "",
  "post_date": "2024-04-29T04:07:04.471974100Z",
  "votes": 1,
  "comment_count": 1,
  "views": 0,
  "content": "<p>\"Given that hyperparameter tuning on Kaggle kernels often requires a lengthy computation time, I'm considering uploading the best LightGBM parameters trained on my local PC to bypass the tuning process in the Kaggle environment. Is this strategy permissible under Kaggle competition rules?\"</p>",
  "messages": [
    {
      "id": "2781898",
      "postDate": "04/29/2024 04:07:04",
      "content": "<p>\"Given that hyperparameter tuning on Kaggle kernels often requires a lengthy computation time, I'm considering uploading the best LightGBM parameters trained on my local PC to bypass the tuning process in the Kaggle environment. Is this strategy permissible under Kaggle competition rules?\"</p>",
      "rawMarkdown": "\"Given that hyperparameter tuning on Kaggle kernels often requires a lengthy computation time, I'm considering uploading the best LightGBM parameters trained on my local PC to bypass the tuning process in the Kaggle environment. Is this strategy permissible under Kaggle competition rules?\"",
      "votes": null
    },
    {
      "id": "2781958",
      "postDate": "04/29/2024 04:49:28",
      "content": "<blockquote>\n  <p>Is this strategy permissible under Kaggle competition rules?\"<br>\n  Yes, sure</p>\n</blockquote>",
      "rawMarkdown": "> Is this strategy permissible under Kaggle competition rules?\"\nYes, sure",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2781958,
      "author_name": "alexxanderlarko",
      "author_url": "",
      "post_date": "04/29/2024 04:49:28",
      "content": "<blockquote>\n  <p>Is this strategy permissible under Kaggle competition rules?\"<br>\n  Yes, sure</p>\n</blockquote>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2781898": "\"Given that hyperparameter tuning on Kaggle kernels often requires a lengthy computation time, I'm considering uploading the best LightGBM parameters trained on my local PC to bypass the tuning process in the Kaggle environment. Is this strategy permissible under Kaggle competition rules?\"",
    "2781958": "> Is this strategy permissible under Kaggle competition rules?\"\nYes, sure"
  },
  "source": "meta"
}