5.7 Exercise
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University of California, Los Angeles *
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Course
MISC
Subject
Industrial Engineering
Date
Feb 20, 2024
Type
docx
Pages
3
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1.
If a customer buys milk, they tend to buy cookies as well. 2.
If a customer buys mustard, they usually buy paper towels with it. 3.
If a customer buys chips, they tend to buy candy bars as well. 4.
If a customer buys diapers, they tend to buy whipped cream as well.
A: 1.
What trends can you spot immediately in the data?
Milk, ice cream, chips, cookies, mustard, and paper towels are the most popular items to buy. The two people who bought baby formula also bought milk. People bought diapers, towels and baby formula. Buy two cases of diapers get a can of whipped cream for $1 off
Buy one set of these two items, get the second set 40% off
Buy two bags of chips get a candy bar for free
Buy cookies, get milk 50% off
Whipped
cream
Diapers Mustard Paper towels
Chips Candy bars Cookies
Milk
2.
What might be useful ways of organizing the data to allow you to spot more trends?
Displaying a number of times an item was bought by a customer.
3.
Are there any negative associations between products?
According to the receipts, bread, battery, paper, bananas, and pencils were the least bought products. 4.
What additional information might be helpful?
How many people in a family, and what foods they like and don’t like. 5.
Can you imagine scenarios in which sets of products are grouped together?
Whipped cream and ice cream might be bought together so people can make sundaes with their ice cream for dessert. D: 1.
What is the significance of the numbers in the two-way table? How are these different than checkmarks?
The numbers in the two-way table show how many receipts display the number of people who bought two items at the same time.
2.
Why is the diagonal and the area below the diagonal in the two-way table grayed out?
The diagonal is grayed out because no one bought a combination of those items.
3.
How do these modifications relate to the efficiency of the data extraction and storage?
The two-way table shows the number of people who bought certain items together, which can help identify the most popular items, the least popular items, items that are bought together frequently, and how to make deals to promote sales of unpopular items.
4.
What information is easier to extract from the two-way table than the raw extracted receipt data?
The information about products' name and the number of the products is easier to extract from
the two-way table than the raw extracted receipt data. It only shows the products and the number.
5.
What information is lost or obscured when looking only at the two-way table?
The information that is lost during this is which receipt the data originally came from. On the shelves I would put The top shelf will have Diapers and towels. The second shelf will have baby formula. And the last shelf can have baby toys. This will allow parents to quickly find the most commonly bought baby items since they will all be in the same place.
E: 1.
How do you know which items should be antecedents and which should be consequents?
The antecedent and consequent are itemsets, which are sets of items. In other words, the antecedent is a combination of items that are analyzed to determine what other items are implied by this combination. These implied items are the consequent of the analysis.
2.
What is the ideal size for sets of antecedents/consequents?
The ideal size for sets of antecedents/consequents varies depending on the context, aiming for a balance between capturing variability and avoiding overfitting. Typically, sets with 5-10 elements are a reasonable starting point, but the optimal size depends on the problem complexity and available data.
3.
Do any of your rules overlap?
No 4.
Could any overlapping rules be simplified or combined in any way?
I don’t have any overlapping rules
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