data minning
DR.octavio
yourname_fallmain18_chapter5_assignment1.docxITS-632 Intro to Data Mining
Dr. Sherri Brinson
Dept. of Information Technology &
School of Computer and Information Sciences
University of the Cumberlands
Fall Main 2018 - Chapter 5 Assignment
[ Your Name Here ]
As you have read the chapter and watched the lecture on chapter 5 from your textbox, your assignment this week is using the following guidelines:
1. Watch the Apriori Algorithm (Associated Learning) - Fun and Easy Machine Learning by Augmented Startups. Approx. 12 min
2. Data Table
|
TID |
Bread |
Peanuts |
Milk |
Fruit |
Jam |
Soda |
Chips |
Cheese |
Yogurt |
|
1 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
0 |
0 |
|
2 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
|
3 |
1 |
0 |
0 |
0 |
1 |
1 |
1 |
0 |
0 |
|
4 |
0 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
0 |
|
5 |
1 |
0 |
1 |
0 |
1 |
1 |
1 |
0 |
0 |
|
6 |
0 |
0 |
1 |
1 |
0 |
1 |
1 |
0 |
0 |
|
7 |
0 |
1 |
1 |
1 |
0 |
1 |
0 |
0 |
0 |
|
8 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
1 |
3. Using the market basket data above, answer the following questions. Make sure you show you work in this document. (Note: Support threshold: 50%)
a. What items represent Itemset (I)?
b. How many transactions in this market basket?
c. What is the support?
d. What is the confidence?
e. What is the lift?
f. What is the conviction?
