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1. What is the Apriori property? 2. Following is a list of five transactions that include items A, B, C, and D: • Tl: {A, B, C} • T2: {A, B} • T3: {B} • T4: {A, C} • TS: {A, C, D} Which itemsets satis
1. What is the Apriori property?
2. Following is a list of five transactions that include items A, B, C, and D:
• Tl: {A, B, C}
• T2: {A, B}
• T3: {B}
• T4: {A, C}
• TS: {A, C, D}
Which itemsets satisfy the minimum support of 0.5?
(Hint: An item set may include more than one item.)
3. How are interesting rules distinguished from coincidental rules?
4. A local retailer has a database that stores 10,000 transactions of last summer. After analyzing the data, a data science team has identified the following statistics:
• {battery} appears in 4,000 transactions.
• {sunscreen} appears in 3,000 transactions.
• {sandals} appears in 4,000 transactions.
• {bowls} appears in 1,000 transactions.
• {battery, sunscreen} appears in 1,500 transactions.
• {battery, sandals} appears in 1,000 transactions.
• {battery, bowls} appears in 1250 transactions.
• {battery, sunscreen, sandals} appears in 600 transactions.
Answer the following questions:
a. What are the support values of the preceding itemsets?
b. Assuming the minimum support is 0.05, which itemsets are considered frequent?
c. What are the confidence values of {battery}->{ sunscreen} and {battery, sunscreen}->{ sandals} ?
d. Which of the two rules is more interesting?
5. In the use of a categorical variable with n possible values, explain the following:
a. Why only n - 1 binary variables are necessary
b. Why using n variables would be problematic
6. If the probability of an event occurring is 0.4, then
a. What is the odds ratio?
b. What is the log odds ratio?
