1. Prepare a summary of the paper containing the following sections (You may use bullet points to summarize multiple points if you wish.) (Hint: Be mindful of the bolded phrases below.):
2. Generate an R data frame from the bank-full.csv file. Submit a screen shot. Hint: One way of doing this is to bring up RStudio. Point it to the working directory where the csv and text files are. Import the csv file using RStudio. Using the console or packages in RStudio bring up Rattle. Now Rattle will be able to see the data frame (R dataset / Data name bank.full).
3. Partition the data frame into a 70/30 split using 42 as the seed.Submit a screen shot.
4. Execute an Exploratory Data Analysis of your choosing. Submit screen shot(s) and a summary of what you have found.
5. Generate a decision tree model using the defaults. Submit screen shot(s) and a summary of what you have found.
6. Evaluate it with ROC and Lift curves. Submit screen shot(s) and a summary of what you have found.
7. Generate a random forest model using the defaults. Submit screen shot(s) and a summary of what you have found.
8. Evaluate it with ROC and Lift curves. Submit screen shot(s) and a summary of what you have found.
9. Generate a support vector machine model using the defaults.Submit screen shot(s) and a summary of what you have found.
10. Evaluate it with ROC and Lift curves. Submit screen shot(s) and a summary of what you have found.
11. If this were your data which model would you recommend be implemented in your bank? Why?
12. Prepare a description of what you have learned and how long it has taken you to do it.
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