{
  "id": 400554,
  "title": "Training Model",
  "url": "/competitions/tlvmc-parkinsons-freezing-gait-prediction/discussion/400554",
  "author_name": "",
  "post_date": "2023-04-09T04:08:25.933331800Z",
  "votes": 1,
  "comment_count": 2,
  "views": 0,
  "content": "<p>Training each model for tdcsfog and defog is more effective than training together for these two datasets???</p>\n<p>When I separate and train the individual models. My result is 1 less precision loss than general training.</p>\n<p>This is related to defog and tdcsfog's distributive learning. When training individually for each dataset, the model cannot learn the association between them.</p>\n<p>It's still an issue that comes to my mind.</p>",
  "messages": [
    {
      "id": "2215050",
      "postDate": "04/09/2023 04:08:25",
      "content": "<p>Training each model for tdcsfog and defog is more effective than training together for these two datasets???</p>\n<p>When I separate and train the individual models. My result is 1 less precision loss than general training.</p>\n<p>This is related to defog and tdcsfog's distributive learning. When training individually for each dataset, the model cannot learn the association between them.</p>\n<p>It's still an issue that comes to my mind.</p>",
      "rawMarkdown": "Training each model for tdcsfog and defog is more effective than training together for these two datasets???\n\nWhen I separate and train the individual models. My result is 1 less precision loss than general training.\n\nThis is related to defog and tdcsfog's distributive learning. When training individually for each dataset, the model cannot learn the association between them.\n\nIt's still an issue that comes to my mind.",
      "votes": null
    },
    {
      "id": "2218203",
      "postDate": "04/11/2023 13:52:50",
      "content": "<p><a href=\"https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction/discussion/396926\" target=\"_blank\">https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction/discussion/396926</a></p>",
      "rawMarkdown": "https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction/discussion/396926",
      "votes": null
    },
    {
      "id": "2218291",
      "postDate": "04/11/2023 14:57:16",
      "content": "<p>Thanks for detailed link. Enjoy this competition. 💪💪💪</p>",
      "rawMarkdown": "Thanks for detailed link. Enjoy this competition. 💪💪💪",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2218203,
      "author_name": "albertoannoni",
      "author_url": "",
      "post_date": "04/11/2023 13:52:50",
      "content": "<p><a href=\"https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction/discussion/396926\" target=\"_blank\">https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction/discussion/396926</a></p>",
      "votes": null,
      "replies": [
        {
          "id": 2218291,
          "author_name": "jjleesunny",
          "author_url": "",
          "post_date": "04/11/2023 14:57:16",
          "content": "<p>Thanks for detailed link. Enjoy this competition. 💪💪💪</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "2215050": "Training each model for tdcsfog and defog is more effective than training together for these two datasets???\n\nWhen I separate and train the individual models. My result is 1 less precision loss than general training.\n\nThis is related to defog and tdcsfog's distributive learning. When training individually for each dataset, the model cannot learn the association between them.\n\nIt's still an issue that comes to my mind.",
    "2218203": "https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction/discussion/396926",
    "2218291": "Thanks for detailed link. Enjoy this competition. 💪💪💪"
  },
  "source": "meta"
}