question archive Option #1: Credit Data Mining In this Portfolio Project, you will analyze credit worthiness
Option #1: Credit Data Mining In this Portfolio Project, you will analyze credit worthiness
Subject:Computer SciencePrice: Bought3
Option #1: Credit Data Mining
In this Portfolio Project, you will analyze credit worthiness. Your assignment submission will be an R Markdown generated Word document.
Create a new R Markdown file by performing the following steps.
1. Open R Studio
2. Select File | New | R Markdown
3. Use MIS 510 Portfolio Project Option 1 as the Title
4. Use your name as the Author
5. Select the Word output format
6. Delete all default content after the R Setup block of code, which is all content from line 12 through the end of the file.
Refer to section 21.2 for background on the GermanCredit.csv file. Explore GermanCredit.csv (Links to an external site.) by performing the following steps.
1. Apply what you learned in this course about data exploration by selecting and running appropriate data exploration functions. Run at least five functions.
2. For your assignment submission, copy your commands into your R Markdown file.
a. Include R comments on all your code.
b. Separate sections of R code by using appropriate R Markdown headings.
3. Divide the data into training and validation partitions.
4. Choose two of the following data mining techniques to explore classification models of this data.
a. Logistic regression
b. Classification trees
c. Neural networks.
5. Analyze your results.
6. Include appropriate visualizations in your analysis.
7. For your assignment submission, copy your commands into your R Markdown file.
a. Include R comments on all your code.
b. Separate sections of R code by using appropriate R Markdown headings.
8. Use the R Markdown Knit drop-down menu to select Knit to Word to create the Word document for your assignment submission.
Your assignment submission must be one Word document that meets the following requirements:
· Is an R Markdown generated Word document containing all R code used in this assignment, appropriate R comments on code, and appropriate R Markdown headings.
· Does not include a cover page.
· Does not include an abstract.
· Includes a one-page description of what you did and what you learned. Add this description to the end of the R Markdown document as a new page. This page must conform to APA guidelines in the CSU Global Writing Center (Links to an external site.).
