Gensim deaccent() vs sklearn strip_accents_unicode()
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Gensim and Scikit-learn both include a function to "remove accents" from Unicode text. However the implementations differ slightly. What, practically, is the difference between them, if any?
Here is the Gensim version:
norm = unicodedata.normalize("NFD", text)
result = ''.join(ch for ch in norm if unicodedata.category(ch) != 'Mn')
return unicodedata.normalize("NFC", result)
And the Scikit-learn version:
normalized = unicodedata.normalize('NFKD', s)
if normalized == s:
return s
else:
return ''.join([c for c in normalized if not unicodedata.combining(c)])
python text unicode scikit-learn gensim
asked Nov 19 at 16:19
shadowtalker
4,32212047
add a comment |
up vote
0
down vote
favorite
Gensim and Scikit-learn both include a function to "remove accents" from Unicode text. However the implementations differ slightly. What, practically, is the difference between them, if any?
Here is the Gensim version:
norm = unicodedata.normalize("NFD", text)
result = ''.join(ch for ch in norm if unicodedata.category(ch) != 'Mn')
return unicodedata.normalize("NFC", result)
And the Scikit-learn version:
normalized = unicodedata.normalize('NFKD', s)
if normalized == s:
return s
else:
return ''.join([c for c in normalized if not unicodedata.combining(c)])
python text unicode scikit-learn gensim
asked Nov 19 at 16:19
shadowtalker
4,32212047
I'd say the Scikit version is broken, as it won't remove accents from strings that are in NFKD form already.
– lenz
Nov 20 at 10:25
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Gensim and Scikit-learn both include a function to "remove accents" from Unicode text. However the implementations differ slightly. What, practically, is the difference between them, if any?
Here is the Gensim version:
norm = unicodedata.normalize("NFD", text)
result = ''.join(ch for ch in norm if unicodedata.category(ch) != 'Mn')
return unicodedata.normalize("NFC", result)
And the Scikit-learn version:
normalized = unicodedata.normalize('NFKD', s)
if normalized == s:
return s
else:
return ''.join([c for c in normalized if not unicodedata.combining(c)])
python text unicode scikit-learn gensim
asked Nov 19 at 16:19
shadowtalker
4,32212047
Gensim and Scikit-learn both include a function to "remove accents" from Unicode text. However the implementations differ slightly. What, practically, is the difference between them, if any?
Here is the Gensim version:
norm = unicodedata.normalize("NFD", text)
result = ''.join(ch for ch in norm if unicodedata.category(ch) != 'Mn')
return unicodedata.normalize("NFC", result)
And the Scikit-learn version:
normalized = unicodedata.normalize('NFKD', s)
if normalized == s:
return s
else:
return ''.join([c for c in normalized if not unicodedata.combining(c)])
python text unicode scikit-learn gensim
python text unicode scikit-learn gensim
asked Nov 19 at 16:19
shadowtalker
4,32212047
asked Nov 19 at 16:19
shadowtalker
4,32212047
asked Nov 19 at 16:19
shadowtalker
4,32212047
asked Nov 19 at 16:19
shadowtalker
4,32212047
asked Nov 19 at 16:19
shadowtalker
4,32212047
4,32212047
I'd say the Scikit version is broken, as it won't remove accents from strings that are in NFKD form already.
– lenz
Nov 20 at 10:25
add a comment |
I'd say the Scikit version is broken, as it won't remove accents from strings that are in NFKD form already.
– lenz
Nov 20 at 10:25
I'd say the Scikit version is broken, as it won't remove accents from strings that are in NFKD form already.
– lenz
Nov 20 at 10:25
I'd say the Scikit version is broken, as it won't remove accents from strings that are in NFKD form already.
– lenz
Nov 20 at 10:25
add a comment |
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I'd say the Scikit version is broken, as it won't remove accents from strings that are in NFKD form already.
– lenz
Nov 20 at 10:25