Difference between revisions of "Come back after 30 days!/Findings"
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*Exploratory data analysis: Thought of the ways to handle 2 variables that have missing values: proposed regression imputation for the variable that has 40% values missing but was cautioned that it may introduce errors. | *Exploratory data analysis: Thought of the ways to handle 2 variables that have missing values: proposed regression imputation for the variable that has 40% values missing but was cautioned that it may introduce errors. | ||
*Consultation with Prof. Kam: | *Consultation with Prof. Kam: | ||
− | ** | + | **For the variable that has 40% missing values, we were advised to conduct a two-pronged approach (i.e. a model without 40% of the data and a model without the variable entirely) in which the eventual models can be used to compare predictive power and therefore, able to make a judgment as to whether the variable was considered a predictor. Were advised that this sort of judgment can be considered as an eventual recommendation. |
+ | **For the variable that has 2.23% missing values, we decide to remove these 2.23% of records which was agreed on the basis of minimal impact | ||
**Apprised of the following steps in data mining process: dummy variables creation, selection of variables for model construction, data sampling & 2 pronged approaches which the team will embark on next. | **Apprised of the following steps in data mining process: dummy variables creation, selection of variables for model construction, data sampling & 2 pronged approaches which the team will embark on next. | ||
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Revision as of 14:42, 7 February 2015
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Summary of findings by week
Week 2 |
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Week 3 |
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Week 4 |
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Week 5 |
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