{
  "id": 238321,
  "title": "What are we penalized more for in the private set?",
  "url": "/competitions/coleridgeinitiative-show-us-the-data/discussion/238321",
  "author_name": "",
  "post_date": "2021-05-11T22:23:27.135452500Z",
  "votes": 7,
  "comment_count": 2,
  "views": 0,
  "content": "<p><a href=\"https://www.kaggle.com/philculliton\" target=\"_blank\">@philculliton</a> </p>\n<p>Are we be penalized more for missing a dataset or predicting an extra dataset or is it the same?</p>\n<p>Thanks,</p>\n<p>Ken</p>",
  "messages": [
    {
      "id": "1303087",
      "postDate": "05/11/2021 22:23:27",
      "content": "<p><a href=\"https://www.kaggle.com/philculliton\" target=\"_blank\">@philculliton</a> </p>\n<p>Are we be penalized more for missing a dataset or predicting an extra dataset or is it the same?</p>\n<p>Thanks,</p>\n<p>Ken</p>",
      "rawMarkdown": "philculliton \n\nAre we be penalized more for missing a dataset or predicting an extra dataset or is it the same?\n\nThanks,\n\nKen",
      "votes": null
    },
    {
      "id": "1303092",
      "postDate": "05/11/2021 22:29:43",
      "content": "<p>Predicting a FP (extra dataset) has a higher penalty than missing a dataset (FN) given the evaluation uses a f-score with beta 0.5.</p>\n<p><a href=\"https://machinelearningmastery.com/fbeta-measure-for-machine-learning/\" target=\"_blank\">https://machinelearningmastery.com/fbeta-measure-for-machine-learning/</a></p>",
      "rawMarkdown": "Predicting a FP (extra dataset) has a higher penalty than missing a dataset (FN) given the evaluation uses a f-score with beta 0.5.\n\nhttps://machinelearningmastery.com/fbeta-measure-for-machine-learning/",
      "votes": null
    },
    {
      "id": "1303098",
      "postDate": "05/11/2021 22:41:38",
      "content": "<p>thanks <a href=\"https://www.kaggle.com/leecming\" target=\"_blank\">@leecming</a> </p>",
      "rawMarkdown": "thanks @leecming",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1303092,
      "author_name": "leecming",
      "author_url": "",
      "post_date": "05/11/2021 22:29:43",
      "content": "<p>Predicting a FP (extra dataset) has a higher penalty than missing a dataset (FN) given the evaluation uses a f-score with beta 0.5.</p>\n<p><a href=\"https://machinelearningmastery.com/fbeta-measure-for-machine-learning/\" target=\"_blank\">https://machinelearningmastery.com/fbeta-measure-for-machine-learning/</a></p>",
      "votes": null,
      "replies": [
        {
          "id": 1303098,
          "author_name": "mlconsult",
          "author_url": "",
          "post_date": "05/11/2021 22:41:38",
          "content": "<p>thanks <a href=\"https://www.kaggle.com/leecming\" target=\"_blank\">@leecming</a> </p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "1303087": "philculliton \n\nAre we be penalized more for missing a dataset or predicting an extra dataset or is it the same?\n\nThanks,\n\nKen",
    "1303092": "Predicting a FP (extra dataset) has a higher penalty than missing a dataset (FN) given the evaluation uses a f-score with beta 0.5.\n\nhttps://machinelearningmastery.com/fbeta-measure-for-machine-learning/",
    "1303098": "thanks @leecming"
  },
  "source": "meta"
}