Difference between revisions of "ANLY482 AY2016-17 T2 Group19 Methodology"
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| − | ==<div style="background: #4d4d4d; padding: 20px; line-height: 0.1em; text-indent: 10px; font-size:20px; font-family: | + | ==<div style="background: #4d4d4d; padding: 20px; line-height: 0.1em; text-indent: 10px; font-size:20px; font-family: Trajan Pro; border-radius: 7px; border-bottom:3px solid #ba3749"><font color= #ffffff>Data Set Acknowledgement</font></div>== |
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-Insert size of data, what time period is it from? (yyyy-yyyy) | -Insert size of data, what time period is it from? (yyyy-yyyy) | ||
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| − | ==<div style="background: #4d4d4d; padding: 20px; line-height: 0.1em; text-indent: 10px; font-size:20px; font-family: | + | ==<div style="background: #4d4d4d; padding: 20px; line-height: 0.1em; text-indent: 10px; font-size:20px; font-family: Trajan Pro; border-radius: 7px; border-bottom:3px solid #ba3749"><font color= #ffffff>-Insert Name of Model</font></div>== |
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Revision as of 19:52, 19 February 2017
Data Set Acknowledgement
-Insert size of data, what time period is it from? (yyyy-yyyy)
-Insert Name of Model
Explanation of the use of this model, why use this, any special treatment done in order to use this model?
Since logistic regression is sensitive to data with skewed distributions, it becomes important to standardize our continuous data to fit a normal distribution as closely as possible. This resulted in balance, duration, campaign, previous and pdays being transformed to provide a better fit for the model.
Steps and approach elaboration
