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Data Mining (assingment)

Data Mining (assingment)

Week 4 Assignment

Complete the following assignment in one MS Word document: 

Chapter 4 – discussion questions #1 through 5 & exercise 1. Note: For exercise 1, if the link provided in the textbook is not working, use this alternative link: https://www.teradata.com/University/Academics
When submitting work, be sure to include an APA cover page and include at least two APA formatted references (and APA in-text citations) to support the work this week.
All work must be original (not copied from any source).

Questions for Discussion

1Define data mining. Why are there many names and definitions for data mining?

Exercises

Teradata University Network (tun) and Other Hands-On Exercises

1.Visit teradatauniversitynetwork.com. Identify case studies and white papers about data mining. Describe recent developments in the field of data mining and predictive modeling.

5. This exercise introduces you to association rule mining. The Excel data set baskets1ntrans.xlsx has around 2,800 observations/records of supermarket transaction products data. Each record contains the customer’s ID and products that they have purchased. Use this data set to understand the relationships among products (i.e., which products are purchased together). Look for interesting relationships and add screenshots of any subtle association patterns that you might find. More specifically, answer the following questions.

Which association rules do you think are most important?

Based on some of the association rules you found, make at least three business recommendations that might be beneficial to the company. These recommendations can include ideas about shelf organization, up-selling, or cross-selling products. (Bonus points will be given to new/innovative ideas.)

What are the Support, Confidence, and Lift values for the following rule?

Wine, Canned Veg→FrozenMeal

(SUBJECT= BUSINESS INTELLIGENCE

BOOK= ANALYTICS, DATA SCIENCE AND ARTIFICIAL INTELLIGENCE

CHAPTER 4= DATA MINING PROCESS,METHODS AND ALGORITHMS)