Question: You are developing a classification model for topics in a large corpus of social media posts. You used a bag of words algorithm to process

You are developing a classification model for topics in a large corpus of social media posts. You used a bag of words algorithm to process your raw text data, but you are not yet satisfied with the model

s performance. You suspect that the number of features is too large for your classifier. Which of the following processes will not be helpful in this situation? A

.

Encoding with bi

-

grams B

.

Removal of stop words C

.

Lemmatization D

.

Term

-

frequency

-

inverse document frequency

(

-

iDF

)

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