Classification: how to handle reviews/long english words in feature set with all other numerical features
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I am currently working on an use case where feature set contains numeric values such as amount, as well as a review feature which contains long winded english text.
the english text will very well differ between train and test data.
eg 'i have seen and its good' , 'nto ok','timepass',etc
how do i combine the text feature set with numerical data and feed it to a machine learning model?
i will nt be able to use encoding , these text variables are not categorical values . they are varying .
machine-learning python classification nltk
asked 19 mins ago
user1906450user1906450
163
$endgroup$
add a comment |
$begingroup$
I am currently working on an use case where feature set contains numeric values such as amount, as well as a review feature which contains long winded english text.
the english text will very well differ between train and test data.
eg 'i have seen and its good' , 'nto ok','timepass',etc
how do i combine the text feature set with numerical data and feed it to a machine learning model?
i will nt be able to use encoding , these text variables are not categorical values . they are varying .
machine-learning python classification nltk
asked 19 mins ago
user1906450user1906450
163
$endgroup$
add a comment |
$begingroup$
I am currently working on an use case where feature set contains numeric values such as amount, as well as a review feature which contains long winded english text.
the english text will very well differ between train and test data.
eg 'i have seen and its good' , 'nto ok','timepass',etc
how do i combine the text feature set with numerical data and feed it to a machine learning model?
i will nt be able to use encoding , these text variables are not categorical values . they are varying .
machine-learning python classification nltk
asked 19 mins ago
user1906450user1906450
163
$endgroup$
I am currently working on an use case where feature set contains numeric values such as amount, as well as a review feature which contains long winded english text.
the english text will very well differ between train and test data.
eg 'i have seen and its good' , 'nto ok','timepass',etc
how do i combine the text feature set with numerical data and feed it to a machine learning model?
i will nt be able to use encoding , these text variables are not categorical values . they are varying .
machine-learning python classification nltk
machine-learning python classification nltk
asked 19 mins ago
user1906450user1906450
163
asked 19 mins ago
user1906450user1906450
163
edited 11 mins ago
user1906450
asked 19 mins ago
user1906450user1906450
163
asked 19 mins ago
user1906450user1906450
163
asked 19 mins ago
user1906450user1906450
163
163
add a comment |
add a comment |
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