{
  "id": 76201,
  "title": "Misspellings",
  "url": "/competitions/quora-insincere-questions-classification/discussion/76201",
  "author_name": "",
  "post_date": "2018-12-30T11:40:04.593632200Z",
  "votes": 3,
  "comment_count": 5,
  "views": 0,
  "content": "<p>Any python library or any idea to deal with misspellings? I am betting it would help improve classifiers.</p>",
  "messages": [
    {
      "id": "447711",
      "postDate": "12/30/2018 11:40:04",
      "content": "<p>Any python library or any idea to deal with misspellings? I am betting it would help improve classifiers.</p>",
      "rawMarkdown": "Any python library or any idea to deal with misspellings? I am betting it would help improve classifiers.",
      "votes": null
    },
    {
      "id": "447898",
      "postDate": "12/30/2018 19:42:55",
      "content": "<p>have you tried pyspellchecker?\n<a href=\"https://pypi.org/project/pyspellchecker/\">https://pypi.org/project/pyspellchecker/</a></p>",
      "rawMarkdown": "have you tried pyspellchecker?\nhttps://pypi.org/project/pyspellchecker/",
      "votes": null
    },
    {
      "id": "448114",
      "postDate": "12/31/2018 09:16:23",
      "content": "<p>Or this: \n<a href=\"https://www.kaggle.com/mlwhiz/spell-checker-using-word2vec\">https://www.kaggle.com/mlwhiz/spell-checker-using-word2vec</a></p>",
      "rawMarkdown": "Or this: \nhttps://www.kaggle.com/mlwhiz/spell-checker-using-word2vec",
      "votes": null
    },
    {
      "id": "448671",
      "postDate": "01/01/2019 20:09:08",
      "content": "<p>i correct many of them manually but no improvement for me </p>",
      "rawMarkdown": "i correct many of them manually but no improvement for me",
      "votes": null
    },
    {
      "id": "448679",
      "postDate": "01/01/2019 20:38:29",
      "content": "<p>I'm using the spacy tokenizer and list of punctuation and don't find any obvious oov or misspelled words</p>\n\n<p>My code:</p>\n\n<pre><code>from spacy.lang.en import English\n\npuncts = [',', '.', '\"', ':', ')', '(', '-', '!', '?', '|', ';', \"'\", '$', '&amp;', '/', '[', ']', '&gt;', '%', '=', '#', '*', '+', '\\\\','•',  '~', '@', '£', \n '·', '_', '{', '}', '©', '^', '®', '`',  '&lt;', '→', '°', '€', '™', '›',  '♥', '←', '×', '§', '″', '′', 'Â', '█', '½', 'à', '…', \n '“', '★', '”', '–', '●', 'â', '►', '−', '¢', '²', '¬', '░', '¶', '↑', '±', '¿', '▾', '═', '¦', '║', '―', '¥', '▓', '—', '‹', '─', \n '▒', '：', '¼', '⊕', '▼', '▪', '†', '■', '’', '▀', '¨', '▄', '♫', '☆', 'é', '¯', '♦', '¤', '▲', 'è', '¸', '¾', 'Ã', '⋅', '‘', '∞', \n '∙', '）', '↓', '、', '│', '（', '»', '，', '♪', '╩', '╚', '³', '・', '╦', '╣', '╔', '╗', '▬', '❤', 'ï', 'Ø', '¹', '≤', '‡', '√', ]\n\n\nnlp = English()\ndef tokenize(sentence):\n    sentence = str(sentence)\n    for punct in puncts:\n        sentence = sentence.replace(punct, f' {punct} ')\n        x = nlp(sentence)\n\nreturn [token.text for token in x]\n</code></pre>\n\n<p>Full kernel: <a href=\"https://www.kaggle.com/bkkaggle/quora-check-coverage/notebook\">https://www.kaggle.com/bkkaggle/quora-check-coverage/notebook</a></p>",
      "rawMarkdown": "I'm using the spacy tokenizer and list of punctuation and don't find any obvious oov or misspelled words\n\nMy code:\n\n    from spacy.lang.en import English\n\n    puncts = [',', '.', '\"', ':', ')', '(', '-', '!', '?', '|', ';', \"'\", '$', '&amp;', '/', '[', ']', '&gt;', '%', '=', '#', '*', '+', '\\\\','•',  '~', '@', '£', \n     '·', '_', '{', '}', '©', '^', '®', '`',  '&lt;', '→', '°', '€', '™', '›',  '♥', '←', '×', '§', '″', '′', 'Â', '█', '½', 'à', '…', \n     '“', '★', '”', '–', '●', 'â', '►', '−', '¢', '²', '¬', '░', '¶', '↑', '±', '¿', '▾', '═', '¦', '║', '―', '¥', '▓', '—', '‹', '─', \n     '▒', '：', '¼', '⊕', '▼', '▪', '†', '■', '’', '▀', '¨', '▄', '♫', '☆', 'é', '¯', '♦', '¤', '▲', 'è', '¸', '¾', 'Ã', '⋅', '‘', '∞', \n     '∙', '）', '↓', '、', '│', '（', '»', '，', '♪', '╩', '╚', '³', '・', '╦', '╣', '╔', '╗', '▬', '❤', 'ï', 'Ø', '¹', '≤', '‡', '√', ]\n\n\n    nlp = English()\n    def tokenize(sentence):\n        sentence = str(sentence)\n        for punct in puncts:\n            sentence = sentence.replace(punct, f' {punct} ')\n            x = nlp(sentence)\n\n    return [token.text for token in x]\n\nFull kernel: https://www.kaggle.com/bkkaggle/quora-check-coverage/notebook",
      "votes": null
    },
    {
      "id": "460065",
      "postDate": "01/22/2019 23:11:45",
      "content": "<p>Textblob has a spellchecker; not sure if it is allowed here though</p>",
      "rawMarkdown": "Textblob has a spellchecker; not sure if it is allowed here though",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 447898,
      "author_name": "alialhumaid",
      "author_url": "",
      "post_date": "12/30/2018 19:42:55",
      "content": "<p>have you tried pyspellchecker?\n<a href=\"https://pypi.org/project/pyspellchecker/\">https://pypi.org/project/pyspellchecker/</a></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 448114,
      "author_name": "mlwhiz",
      "author_url": "",
      "post_date": "12/31/2018 09:16:23",
      "content": "<p>Or this: \n<a href=\"https://www.kaggle.com/mlwhiz/spell-checker-using-word2vec\">https://www.kaggle.com/mlwhiz/spell-checker-using-word2vec</a></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 448671,
      "author_name": "sdafweagvdsv",
      "author_url": "",
      "post_date": "01/01/2019 20:09:08",
      "content": "<p>i correct many of them manually but no improvement for me </p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 448679,
      "author_name": "bkkaggle",
      "author_url": "",
      "post_date": "01/01/2019 20:38:29",
      "content": "<p>I'm using the spacy tokenizer and list of punctuation and don't find any obvious oov or misspelled words</p>\n\n<p>My code:</p>\n\n<pre><code>from spacy.lang.en import English\n\npuncts = [',', '.', '\"', ':', ')', '(', '-', '!', '?', '|', ';', \"'\", '$', '&amp;', '/', '[', ']', '&gt;', '%', '=', '#', '*', '+', '\\\\','•',  '~', '@', '£', \n '·', '_', '{', '}', '©', '^', '®', '`',  '&lt;', '→', '°', '€', '™', '›',  '♥', '←', '×', '§', '″', '′', 'Â', '█', '½', 'à', '…', \n '“', '★', '”', '–', '●', 'â', '►', '−', '¢', '²', '¬', '░', '¶', '↑', '±', '¿', '▾', '═', '¦', '║', '―', '¥', '▓', '—', '‹', '─', \n '▒', '：', '¼', '⊕', '▼', '▪', '†', '■', '’', '▀', '¨', '▄', '♫', '☆', 'é', '¯', '♦', '¤', '▲', 'è', '¸', '¾', 'Ã', '⋅', '‘', '∞', \n '∙', '）', '↓', '、', '│', '（', '»', '，', '♪', '╩', '╚', '³', '・', '╦', '╣', '╔', '╗', '▬', '❤', 'ï', 'Ø', '¹', '≤', '‡', '√', ]\n\n\nnlp = English()\ndef tokenize(sentence):\n    sentence = str(sentence)\n    for punct in puncts:\n        sentence = sentence.replace(punct, f' {punct} ')\n        x = nlp(sentence)\n\nreturn [token.text for token in x]\n</code></pre>\n\n<p>Full kernel: <a href=\"https://www.kaggle.com/bkkaggle/quora-check-coverage/notebook\">https://www.kaggle.com/bkkaggle/quora-check-coverage/notebook</a></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 460065,
      "author_name": "agnedil",
      "author_url": "",
      "post_date": "01/22/2019 23:11:45",
      "content": "<p>Textblob has a spellchecker; not sure if it is allowed here though</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "447711": "Any python library or any idea to deal with misspellings? I am betting it would help improve classifiers.",
    "447898": "have you tried pyspellchecker?\nhttps://pypi.org/project/pyspellchecker/",
    "448114": "Or this: \nhttps://www.kaggle.com/mlwhiz/spell-checker-using-word2vec",
    "448671": "i correct many of them manually but no improvement for me",
    "448679": "I'm using the spacy tokenizer and list of punctuation and don't find any obvious oov or misspelled words\n\nMy code:\n\n    from spacy.lang.en import English\n\n    puncts = [',', '.', '\"', ':', ')', '(', '-', '!', '?', '|', ';', \"'\", '$', '&amp;', '/', '[', ']', '&gt;', '%', '=', '#', '*', '+', '\\\\','•',  '~', '@', '£', \n     '·', '_', '{', '}', '©', '^', '®', '`',  '&lt;', '→', '°', '€', '™', '›',  '♥', '←', '×', '§', '″', '′', 'Â', '█', '½', 'à', '…', \n     '“', '★', '”', '–', '●', 'â', '►', '−', '¢', '²', '¬', '░', '¶', '↑', '±', '¿', '▾', '═', '¦', '║', '―', '¥', '▓', '—', '‹', '─', \n     '▒', '：', '¼', '⊕', '▼', '▪', '†', '■', '’', '▀', '¨', '▄', '♫', '☆', 'é', '¯', '♦', '¤', '▲', 'è', '¸', '¾', 'Ã', '⋅', '‘', '∞', \n     '∙', '）', '↓', '、', '│', '（', '»', '，', '♪', '╩', '╚', '³', '・', '╦', '╣', '╔', '╗', '▬', '❤', 'ï', 'Ø', '¹', '≤', '‡', '√', ]\n\n\n    nlp = English()\n    def tokenize(sentence):\n        sentence = str(sentence)\n        for punct in puncts:\n            sentence = sentence.replace(punct, f' {punct} ')\n            x = nlp(sentence)\n\n    return [token.text for token in x]\n\nFull kernel: https://www.kaggle.com/bkkaggle/quora-check-coverage/notebook",
    "460065": "Textblob has a spellchecker; not sure if it is allowed here though"
  },
  "source": "meta"
}