{
  "id": 72332,
  "title": "Spelling mistakes???",
  "url": "/competitions/quora-insincere-questions-classification/discussion/72332",
  "author_name": "",
  "post_date": "2018-11-22T10:32:20.838698700Z",
  "votes": null,
  "comment_count": 11,
  "views": 0,
  "content": "<p>Is their any way to easily deal with spelling mistakes.</p>",
  "messages": [
    {
      "id": "425932",
      "postDate": "11/22/2018 10:32:20",
      "content": "<p>Is their any way to easily deal with spelling mistakes.</p>",
      "rawMarkdown": "Is their any way to easily deal with spelling mistakes.",
      "votes": null
    },
    {
      "id": "425937",
      "postDate": "11/22/2018 10:39:51",
      "content": "<p>You can use a dictionary of the form {mistake : correction}, I believe there is some online.</p>\n\n<p>Then apply the following transformation for all texts and for all possible mistakes :</p>\n\n<p><code>x = x.replace(word, dic[word])</code></p>",
      "rawMarkdown": "You can use a dictionary of the form {mistake : correction}, I believe there is some online.\n\nThen apply the following transformation for all texts and for all possible mistakes :\n\n``` x = x.replace(word, dic[word]) ```",
      "votes": null
    },
    {
      "id": "425954",
      "postDate": "11/22/2018 10:59:43",
      "content": "<p>Hello Nikhil,</p>\n\n<p>There are several packages to help you dealing with spelling mistakes. For example I sometime use this one which should help you : <a href=\"https://github.com/barrust/pyspellchecker\">https://github.com/barrust/pyspellchecker</a></p>",
      "rawMarkdown": "Hello Nikhil,\n\nThere are several packages to help you dealing with spelling mistakes. For example I sometime use this one which should help you : https://github.com/barrust/pyspellchecker",
      "votes": null
    },
    {
      "id": "426129",
      "postDate": "11/22/2018 17:08:24",
      "content": "<p>For sure there are online ones, but due to forbidden use of external data in this competition it makes them useless from this point of view.</p>",
      "rawMarkdown": "For sure there are online ones, but due to forbidden use of external data in this competition it makes them useless from this point of view.",
      "votes": null
    },
    {
      "id": "426624",
      "postDate": "11/23/2018 14:58:57",
      "content": "<p>can we hardcode the dictionary?</p>",
      "rawMarkdown": "can we hardcode the dictionary?",
      "votes": null
    },
    {
      "id": "426653",
      "postDate": "11/23/2018 15:43:54",
      "content": "<p>Hardcoding is not using external data.\nAs mentioned here: <a href=\"https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/72120\">https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/72120</a>  it may be feasible to prepare such not too long hardcoded dictionary for this specific use of this competion.</p>",
      "rawMarkdown": "Hardcoding is not using external data.\nAs mentioned here: https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/72120  it may be feasible to prepare such not too long hardcoded dictionary for this specific use of this competion.",
      "votes": null
    },
    {
      "id": "426944",
      "postDate": "11/24/2018 08:05:41",
      "content": "<p>thank you</p>",
      "rawMarkdown": "thank you",
      "votes": null
    },
    {
      "id": "428202",
      "postDate": "11/26/2018 23:02:03",
      "content": "<p>You could use hunspell is part of the kaggle docker image.</p>",
      "rawMarkdown": "You could use hunspell is part of the kaggle docker image.",
      "votes": null
    },
    {
      "id": "428236",
      "postDate": "11/27/2018 00:56:04",
      "content": "<p>I used the Levenshtein distance to match any word that is not in an embedding by its closest neighbor (it's usually a one letter difference or so). It didn't improve my score though, strangely.</p>",
      "rawMarkdown": "I used the Levenshtein distance to match any word that is not in an embedding by its closest neighbor (it's usually a one letter difference or so). It didn't improve my score though, strangely.",
      "votes": null
    },
    {
      "id": "428238",
      "postDate": "11/27/2018 00:58:37",
      "content": "<p>are we sure hardcoding is not against the rules? Using a pre-computed match dictionary instead of computing it during runtime seems like a way to bypass the time limit (not judging, just curious)</p>",
      "rawMarkdown": "are we sure hardcoding is not against the rules? Using a pre-computed match dictionary instead of computing it during runtime seems like a way to bypass the time limit (not judging, just curious)",
      "votes": null
    },
    {
      "id": "428507",
      "postDate": "11/27/2018 11:54:33",
      "content": "<p>It would be really hard to define and impractical to judge if anything hardcoded is violating rules. Therefore I assume all hardcoding is allowed even if the values you enter were calculated in your previous kernels or offline.</p>",
      "rawMarkdown": "It would be really hard to define and impractical to judge if anything hardcoded is violating rules. Therefore I assume all hardcoding is allowed even if the values you enter were calculated in your previous kernels or offline.",
      "votes": null
    },
    {
      "id": "437397",
      "postDate": "12/11/2018 20:37:55",
      "content": "<p>External data is not allowed in this competition. Though, would that be considered external data or a standard tool?</p>",
      "rawMarkdown": "External data is not allowed in this competition. Though, would that be considered external data or a standard tool?",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 425937,
      "author_name": "theoviel",
      "author_url": "",
      "post_date": "11/22/2018 10:39:51",
      "content": "<p>You can use a dictionary of the form {mistake : correction}, I believe there is some online.</p>\n\n<p>Then apply the following transformation for all texts and for all possible mistakes :</p>\n\n<p><code>x = x.replace(word, dic[word])</code></p>",
      "votes": null,
      "replies": [
        {
          "id": 426129,
          "author_name": "akuropatwinski",
          "author_url": "",
          "post_date": "11/22/2018 17:08:24",
          "content": "<p>For sure there are online ones, but due to forbidden use of external data in this competition it makes them useless from this point of view.</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 426624,
          "author_name": "eavdeeva",
          "author_url": "",
          "post_date": "11/23/2018 14:58:57",
          "content": "<p>can we hardcode the dictionary?</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 426653,
          "author_name": "akuropatwinski",
          "author_url": "",
          "post_date": "11/23/2018 15:43:54",
          "content": "<p>Hardcoding is not using external data.\nAs mentioned here: <a href=\"https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/72120\">https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/72120</a>  it may be feasible to prepare such not too long hardcoded dictionary for this specific use of this competion.</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 426944,
          "author_name": "eavdeeva",
          "author_url": "",
          "post_date": "11/24/2018 08:05:41",
          "content": "<p>thank you</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 428202,
          "author_name": "agentili",
          "author_url": "",
          "post_date": "11/26/2018 23:02:03",
          "content": "<p>You could use hunspell is part of the kaggle docker image.</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 428238,
          "author_name": "pforet95",
          "author_url": "",
          "post_date": "11/27/2018 00:58:37",
          "content": "<p>are we sure hardcoding is not against the rules? Using a pre-computed match dictionary instead of computing it during runtime seems like a way to bypass the time limit (not judging, just curious)</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 428507,
          "author_name": "akuropatwinski",
          "author_url": "",
          "post_date": "11/27/2018 11:54:33",
          "content": "<p>It would be really hard to define and impractical to judge if anything hardcoded is violating rules. Therefore I assume all hardcoding is allowed even if the values you enter were calculated in your previous kernels or offline.</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 425954,
      "author_name": "xtelima",
      "author_url": "",
      "post_date": "11/22/2018 10:59:43",
      "content": "<p>Hello Nikhil,</p>\n\n<p>There are several packages to help you dealing with spelling mistakes. For example I sometime use this one which should help you : <a href=\"https://github.com/barrust/pyspellchecker\">https://github.com/barrust/pyspellchecker</a></p>",
      "votes": null,
      "replies": [
        {
          "id": 437397,
          "author_name": "pointyointment",
          "author_url": "",
          "post_date": "12/11/2018 20:37:55",
          "content": "<p>External data is not allowed in this competition. Though, would that be considered external data or a standard tool?</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 428236,
      "author_name": "pforet95",
      "author_url": "",
      "post_date": "11/27/2018 00:56:04",
      "content": "<p>I used the Levenshtein distance to match any word that is not in an embedding by its closest neighbor (it's usually a one letter difference or so). It didn't improve my score though, strangely.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "425932": "Is their any way to easily deal with spelling mistakes.",
    "425937": "You can use a dictionary of the form {mistake : correction}, I believe there is some online.\n\nThen apply the following transformation for all texts and for all possible mistakes :\n\n``` x = x.replace(word, dic[word]) ```",
    "425954": "Hello Nikhil,\n\nThere are several packages to help you dealing with spelling mistakes. For example I sometime use this one which should help you : https://github.com/barrust/pyspellchecker",
    "426129": "For sure there are online ones, but due to forbidden use of external data in this competition it makes them useless from this point of view.",
    "426624": "can we hardcode the dictionary?",
    "426653": "Hardcoding is not using external data.\nAs mentioned here: https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/72120  it may be feasible to prepare such not too long hardcoded dictionary for this specific use of this competion.",
    "426944": "thank you",
    "428202": "You could use hunspell is part of the kaggle docker image.",
    "428236": "I used the Levenshtein distance to match any word that is not in an embedding by its closest neighbor (it's usually a one letter difference or so). It didn't improve my score though, strangely.",
    "428238": "are we sure hardcoding is not against the rules? Using a pre-computed match dictionary instead of computing it during runtime seems like a way to bypass the time limit (not judging, just curious)",
    "428507": "It would be really hard to define and impractical to judge if anything hardcoded is violating rules. Therefore I assume all hardcoding is allowed even if the values you enter were calculated in your previous kernels or offline.",
    "437397": "External data is not allowed in this competition. Though, would that be considered external data or a standard tool?"
  },
  "source": "meta"
}