3. In an area there is a modern that sells various types of snacks. Specified min_sup = 50% and confidence = 80%. Based on the list of transactions in the transaction table in Table 1 below: a. Determine all frequent itemsets using the Apriori algorithm Note: When working on the problem, DO NOT change: the name of the item MUST be written according to what is in the question TID Name of goods T100 {A, B, E, C} T200 {D, F, G, H, I} T300 {J, F, I, H} T400 {I. B. E}

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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DATA MINING

3. In an area there is a modern that sells various types of snacks. Specified min sup = 50% and
confidence = 80%. Based on the list of transactions in the transaction table in Table 1 below:
a. Determine all frequent itemsets using the Apriori algorithm
Note: When working on the problem, DO NOT change: the name of the item MUST be written
according to what is in the question
TID
Name of goods
T100
{A, B, E, C}
T200
{D, F, G, H, I}
Т300
{J, F, I, H}
T400
{1, В, Е}
Transcribed Image Text:3. In an area there is a modern that sells various types of snacks. Specified min sup = 50% and confidence = 80%. Based on the list of transactions in the transaction table in Table 1 below: a. Determine all frequent itemsets using the Apriori algorithm Note: When working on the problem, DO NOT change: the name of the item MUST be written according to what is in the question TID Name of goods T100 {A, B, E, C} T200 {D, F, G, H, I} Т300 {J, F, I, H} T400 {1, В, Е}
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