I have a set of incidents with certain text named short description (text is in bilingual) with [login to view URL] updates.
Now, I want to predict [login to view URL] updates for a new incident based on past incident data sets.
a) Cleaning the short description column
b) Creating two columns for each language separately
2) Prediction model from past data
a) Calculating TF-IDF value individually for each language
b) Estimation the category(as either High/Low) based on Naive Bayes classifier(F1-measure)
Data format: CSV
Data size: 11200 rows
no. of updates class for categorizing :
1)High--if updates >= 12
2)Low--if upddates <12
Further details will be sent personally
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