Difference between revisions of "APA Feature Engineering"
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# Each subject line of an email will then have an aggregated weightage of the terms appearing in itself. | # Each subject line of an email will then have an aggregated weightage of the terms appearing in itself. | ||
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− | [[Image:Subjectlineweightagescreenshot.jpg| | + | [[Image:Subjectlineweightagescreenshot.jpg|800px]] |
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'''Email Exchange Ratio:'''<br> | '''Email Exchange Ratio:'''<br> |
Revision as of 04:45, 22 February 2017
Subject Line weightage: We will be using subject line weightage as one of the components in determining how important and relevant a single email exchange is to the business. Our approach will be as follows:
- First run an analysis on all the terms occurring in the entire dataset
- This analysis will filter out common words, prepositions and other unimportant words that could potentially skew the results.
- The analysis will return a listen of words along with the frequency of the term’s occurrence in the dataset.
- Based on the results obtained, we would like to calculate the tf-idf of each term.
- tf: how often does the term occur in the document
- idf: how often does the term occur in other documents
- tf-idf will allow us to find the most important terms in the set of documents
- Using the value of this tf-idf, we will assign each term a weightage based on how important it is in determining the importance to the business
- Each subject line of an email will then have an aggregated weightage of the terms appearing in itself.
Email Exchange Ratio:
This metric will show the number of emails exchanged between the two employees as a ratio of the total number of emails exchanged by these employees.
- isForward?: Will indicate whether the email was forwarded to the recipient
- isReply?: Will indicate whether the email was a reply