{
  "id": 395090,
  "title": "Sørensen–Dice index, F1 score, Czekanowski's binary, Zijdenbos similarity. Many names, same DICE.",
  "url": "/competitions/vesuvius-challenge-ink-detection/discussion/395090",
  "author_name": "",
  "post_date": "2023-03-15T20:15:16.359146300Z",
  "votes": 7,
  "comment_count": 2,
  "views": 0,
  "content": "<p>\"The index is known by several other names, especially Sørensen–Dice index, Sørensen index and Dice's coefficient. Other variations include the \"similarity coefficient\" or \"index\", such as Dice similarity coefficient (DSC).\"</p>\n<p>\"Other names include:</p>\n<p>F1 score<br>\nCzekanowski's binary (non-quantitative) index<br>\nMeasure of genetic similarity<br>\nZijdenbos similarity index, referring to a 1994 paper of Zijdenbos et al.</p>\n<p>\"The Sørensen–Dice coefficient is a statistic used to gauge the similarity of two samples. It was independently developed by the botanists Thorvald Sørensen and Lee Raymond Dice, who published in 1948 and 1945 respectively.\"</p>\n<p>APPLICATIONS </p>\n<p>\"The Sørensen–Dice coefficient is useful for ecological community data. . As compared to Euclidean distance, the Sørensen distance retains sensitivity in more heterogeneous data sets and gives less weight to outliers.\"</p>\n<p>\" Recently the Dice score (and its variations, e.g. logDice taking a logarithm of it) has become popular in computer lexicography for measuring the lexical association score of two given words. logDice is also used as part of the Mash Distance for genome and metagenome distance estimation Finally, Dice is used in image segmentation, in particular for comparing algorithm output against reference masks in medical applications.\"</p>\n<p><a href=\"https://www.wikiwand.com/en/S%C3%B8rensen%E2%80%93Dice_coefficient\" target=\"_blank\">https://www.wikiwand.com/en/S%C3%B8rensen%E2%80%93Dice_coefficient</a></p>\n<h1>Writing a simple DICE Coefficient Implementation (By Kaggler Yerram Varun)</h1>\n<p>def DICE_COE(mask1, mask2):<br>\n    intersect = np.sum(mask1*mask2)<br>\n    fsum = np.sum(mask1)<br>\n    ssum = np.sum(mask2)<br>\n    dice = (2 * intersect ) / (fsum + ssum)<br>\n    dice = np.mean(dice)<br>\n    dice = round(dice, 3) # for easy reading<br>\n    return dice </p>\n<p><a href=\"https://www.kaggle.com/code/yerramvarun/understanding-dice-coefficient/notebook\" target=\"_blank\">https://www.kaggle.com/code/yerramvarun/understanding-dice-coefficient/notebook</a></p>",
  "messages": [
    {
      "id": "2183677",
      "postDate": "03/15/2023 20:15:16",
      "content": "<p>\"The index is known by several other names, especially Sørensen–Dice index, Sørensen index and Dice's coefficient. Other variations include the \"similarity coefficient\" or \"index\", such as Dice similarity coefficient (DSC).\"</p>\n<p>\"Other names include:</p>\n<p>F1 score<br>\nCzekanowski's binary (non-quantitative) index<br>\nMeasure of genetic similarity<br>\nZijdenbos similarity index, referring to a 1994 paper of Zijdenbos et al.</p>\n<p>\"The Sørensen–Dice coefficient is a statistic used to gauge the similarity of two samples. It was independently developed by the botanists Thorvald Sørensen and Lee Raymond Dice, who published in 1948 and 1945 respectively.\"</p>\n<p>APPLICATIONS </p>\n<p>\"The Sørensen–Dice coefficient is useful for ecological community data. . As compared to Euclidean distance, the Sørensen distance retains sensitivity in more heterogeneous data sets and gives less weight to outliers.\"</p>\n<p>\" Recently the Dice score (and its variations, e.g. logDice taking a logarithm of it) has become popular in computer lexicography for measuring the lexical association score of two given words. logDice is also used as part of the Mash Distance for genome and metagenome distance estimation Finally, Dice is used in image segmentation, in particular for comparing algorithm output against reference masks in medical applications.\"</p>\n<p><a href=\"https://www.wikiwand.com/en/S%C3%B8rensen%E2%80%93Dice_coefficient\" target=\"_blank\">https://www.wikiwand.com/en/S%C3%B8rensen%E2%80%93Dice_coefficient</a></p>\n<h1>Writing a simple DICE Coefficient Implementation (By Kaggler Yerram Varun)</h1>\n<p>def DICE_COE(mask1, mask2):<br>\n    intersect = np.sum(mask1*mask2)<br>\n    fsum = np.sum(mask1)<br>\n    ssum = np.sum(mask2)<br>\n    dice = (2 * intersect ) / (fsum + ssum)<br>\n    dice = np.mean(dice)<br>\n    dice = round(dice, 3) # for easy reading<br>\n    return dice </p>\n<p><a href=\"https://www.kaggle.com/code/yerramvarun/understanding-dice-coefficient/notebook\" target=\"_blank\">https://www.kaggle.com/code/yerramvarun/understanding-dice-coefficient/notebook</a></p>",
      "rawMarkdown": "\"The index is known by several other names, especially Sørensen–Dice index, Sørensen index and Dice's coefficient. Other variations include the \"similarity coefficient\" or \"index\", such as Dice similarity coefficient (DSC).\"\n\n\"Other names include:\n\nF1 score\nCzekanowski's binary (non-quantitative) index\nMeasure of genetic similarity\nZijdenbos similarity index, referring to a 1994 paper of Zijdenbos et al.\n\n\"The Sørensen–Dice coefficient is a statistic used to gauge the similarity of two samples. It was independently developed by the botanists Thorvald Sørensen and Lee Raymond Dice, who published in 1948 and 1945 respectively.\"\n\nAPPLICATIONS \n\n\"The Sørensen–Dice coefficient is useful for ecological community data. . As compared to Euclidean distance, the Sørensen distance retains sensitivity in more heterogeneous data sets and gives less weight to outliers.\"\n\n\" Recently the Dice score (and its variations, e.g. logDice taking a logarithm of it) has become popular in computer lexicography for measuring the lexical association score of two given words. logDice is also used as part of the Mash Distance for genome and metagenome distance estimation Finally, Dice is used in image segmentation, in particular for comparing algorithm output against reference masks in medical applications.\"\n\nhttps://www.wikiwand.com/en/S%C3%B8rensen%E2%80%93Dice_coefficient\n\n#Writing a simple DICE Coefficient Implementation (By Kaggler Yerram Varun)\n\ndef DICE_COE(mask1, mask2):\n    intersect = np.sum(mask1*mask2)\n    fsum = np.sum(mask1)\n    ssum = np.sum(mask2)\n    dice = (2 * intersect ) / (fsum + ssum)\n    dice = np.mean(dice)\n    dice = round(dice, 3) # for easy reading\n    return dice \n\nhttps://www.kaggle.com/code/yerramvarun/understanding-dice-coefficient/notebook",
      "votes": null
    },
    {
      "id": "2183702",
      "postDate": "03/15/2023 20:46:05",
      "content": "<p>Nice, thank you!</p>",
      "rawMarkdown": "Nice, thank you!",
      "votes": null
    },
    {
      "id": "2184449",
      "postDate": "03/16/2023 11:46:38",
      "content": "<p>You're welcome Jan Paul.</p>",
      "rawMarkdown": "You're welcome Jan Paul.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2183702,
      "author_name": "jpposma",
      "author_url": "",
      "post_date": "03/15/2023 20:46:05",
      "content": "<p>Nice, thank you!</p>",
      "votes": null,
      "replies": [
        {
          "id": 2184449,
          "author_name": "mpwolke",
          "author_url": "",
          "post_date": "03/16/2023 11:46:38",
          "content": "<p>You're welcome Jan Paul.</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "2183677": "\"The index is known by several other names, especially Sørensen–Dice index, Sørensen index and Dice's coefficient. Other variations include the \"similarity coefficient\" or \"index\", such as Dice similarity coefficient (DSC).\"\n\n\"Other names include:\n\nF1 score\nCzekanowski's binary (non-quantitative) index\nMeasure of genetic similarity\nZijdenbos similarity index, referring to a 1994 paper of Zijdenbos et al.\n\n\"The Sørensen–Dice coefficient is a statistic used to gauge the similarity of two samples. It was independently developed by the botanists Thorvald Sørensen and Lee Raymond Dice, who published in 1948 and 1945 respectively.\"\n\nAPPLICATIONS \n\n\"The Sørensen–Dice coefficient is useful for ecological community data. . As compared to Euclidean distance, the Sørensen distance retains sensitivity in more heterogeneous data sets and gives less weight to outliers.\"\n\n\" Recently the Dice score (and its variations, e.g. logDice taking a logarithm of it) has become popular in computer lexicography for measuring the lexical association score of two given words. logDice is also used as part of the Mash Distance for genome and metagenome distance estimation Finally, Dice is used in image segmentation, in particular for comparing algorithm output against reference masks in medical applications.\"\n\nhttps://www.wikiwand.com/en/S%C3%B8rensen%E2%80%93Dice_coefficient\n\n#Writing a simple DICE Coefficient Implementation (By Kaggler Yerram Varun)\n\ndef DICE_COE(mask1, mask2):\n    intersect = np.sum(mask1*mask2)\n    fsum = np.sum(mask1)\n    ssum = np.sum(mask2)\n    dice = (2 * intersect ) / (fsum + ssum)\n    dice = np.mean(dice)\n    dice = round(dice, 3) # for easy reading\n    return dice \n\nhttps://www.kaggle.com/code/yerramvarun/understanding-dice-coefficient/notebook",
    "2183702": "Nice, thank you!",
    "2184449": "You're welcome Jan Paul."
  },
  "source": "meta"
}