FPGROWTH

What is the purpose of the FP Growth algorithm?

• To generate patterns by candidate generation

• To pair items into singletons, pairs, and triplets

• To find compact patterns

• To scan the database for each iteration

What does the Support metric indicate?

• The relevance of the item

• The count of 1-itemsets in the database

• The strength of the relationship between items

• The likelihood of buying Mayo and Burgers together

How does FP Growth differ from Apriori in terms of pattern generation?

• FP Growth uses candidate generation

• Apriori does not generate patterns

• FP Growth generates patterns by pairing items

What is the purpose of constructing the FP tree in the FP Growth algorithm?

• To examine the transactions

• To scan the database for each iteration

• To store the database in a compact version in memory

• To generate frequent patterns

What is the significance of the support count in FP-growth?

• • It determines the ordering of items in transactions.

• • It controls the number of transactions in the dataset.

• • It influences the decision to remove infrequent items.

• • It specifies the maximum depth of the FP-tree.

1. What role does the confidence parameter play in association rule generation?

• • It controls the ordering of items in the FP-tree.

• • It filters out rules with low support.

• • It determines the number of transactions in the dataset.

• • It sets the threshold for rule significance.

Tags

NGSS.MS-ETS1-4