Assignment 6.docx - Assignment Name Advance Predictive Modelling 1 How will you treat text having short cut words(like bcz u thr etc\u2026 Ans After a text

Assignment 6.docx - Assignment Name Advance Predictive...

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Assignment Name - Advance Predictive Modelling 1.How will you treat text having short cut words (like bcz, u, thr etc…)?Ans: After a text is obtained, we start with text normalization. Text normalization includes:Converting all letters to lower or upper case.Converting number into words or removing numbers.Removing punctuations, accent marks, etc.Removing white spacesExpanding abbreviations Removing stop words, spares terms and particulaer words.Shortcut words can be treated in two waysa.Expand the shortcut words: stemming can bring the words in root form, though stemming object group needs to be defined for these words. Normalization techniques can be applied to expand these words.b.Remove the shortcut words from the text using tokenization in Python or using “re” regex library or stop words list can also be updated to remove these words from text.2.Write R and python code to replace “bcz” with “because” in whole text?
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  • Fall '19
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