{
  "id": 531496,
  "title": "how to calculate score?",
  "url": "/competitions/rsna-2024-lumbar-spine-degenerative-classification/discussion/531496",
  "author_name": "",
  "post_date": "2024-09-01T16:31:13.676835700Z",
  "votes": 1,
  "comment_count": 1,
  "views": 0,
  "content": "<p>I have already trained the model but I don't know how to calculate score.<br>\nthis is the first time I have participate in a kaggle competition.</p>\n<p>According to my observation I know score is not accuracy, f1 score, precision, recall or roc curve.<br>\nSo what is it and how do I calculate?</p>",
  "messages": [
    {
      "id": "2976230",
      "postDate": "09/01/2024 16:31:13",
      "content": "<p>I have already trained the model but I don't know how to calculate score.<br>\nthis is the first time I have participate in a kaggle competition.</p>\n<p>According to my observation I know score is not accuracy, f1 score, precision, recall or roc curve.<br>\nSo what is it and how do I calculate?</p>",
      "rawMarkdown": "I have already trained the model but I don't know how to calculate score.\nthis is the first time I have participate in a kaggle competition.\n\nAccording to my observation I know score is not accuracy, f1 score, precision, recall or roc curve.\nSo what is it and how do I calculate?",
      "votes": null
    },
    {
      "id": "2976373",
      "postDate": "09/01/2024 21:11:04",
      "content": "<p>It's already mentioned in the evaluation section of the overview: Submissions are evaluated using the average of sample-weighted log losses and an any_severe_spinal prediction generated by the metric. The metric notebook can be found at: <a href=\"https://www.kaggle.com/code/metric/rsna-lumbar-metric-71549\" target=\"_blank\">https://www.kaggle.com/code/metric/rsna-lumbar-metric-71549</a> .</p>",
      "rawMarkdown": "It's already mentioned in the evaluation section of the overview: Submissions are evaluated using the average of sample-weighted log losses and an any_severe_spinal prediction generated by the metric. The metric notebook can be found at: https://www.kaggle.com/code/metric/rsna-lumbar-metric-71549 .",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2976373,
      "author_name": "loukilons",
      "author_url": "",
      "post_date": "09/01/2024 21:11:04",
      "content": "<p>It's already mentioned in the evaluation section of the overview: Submissions are evaluated using the average of sample-weighted log losses and an any_severe_spinal prediction generated by the metric. The metric notebook can be found at: <a href=\"https://www.kaggle.com/code/metric/rsna-lumbar-metric-71549\" target=\"_blank\">https://www.kaggle.com/code/metric/rsna-lumbar-metric-71549</a> .</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2976230": "I have already trained the model but I don't know how to calculate score.\nthis is the first time I have participate in a kaggle competition.\n\nAccording to my observation I know score is not accuracy, f1 score, precision, recall or roc curve.\nSo what is it and how do I calculate?",
    "2976373": "It's already mentioned in the evaluation section of the overview: Submissions are evaluated using the average of sample-weighted log losses and an any_severe_spinal prediction generated by the metric. The metric notebook can be found at: https://www.kaggle.com/code/metric/rsna-lumbar-metric-71549 ."
  },
  "source": "meta"
}