A database has four transactions. Let min_sup (^{text {4 }}=60 %) and min_conf (^{text {s }}=80 %).

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A database has four transactions. Let min_sup \(^{\text {4 }}=60 \%\) and min_conf \(^{\text {s }}=80 \%\).

T100 cust_ID TID items_bought (in the form of brand-item_category) 01 (King's-Crab, Sunset-Milk,

a. At the granularity of item_category (e.g., item \({ }_{i}\) could be "Milk"), for the rule template,
\[
\forall X \in \text { transaction, buys }\left(X, \text { item }_{1}ight) \wedge \operatorname{buys}\left(X, \text { item }_{2}ight) \Rightarrow \text { buys }\left(X, \text { item }_{3}ight) \quad[s, c],
\]
list the frequent \(k\)-itemset for the largest \(k\), and all the strong association rules (with their support \(s\) and confidence \(c\) ) containing the frequent \(k\)-itemset for the largest \(k\).
b. At the granularity of brand-item_category (e.g., item \({ }_{i}\) could be "Sunset-Milk"), for the rule template,
\[
\forall X \in \text { customer, } \operatorname{buys}\left(X, \text { item }_{1}ight) \wedge \operatorname{buys}\left(X, \text { item }_{2}ight) \Rightarrow \text { buys }\left(X, \text { item }_{3}ight),
\]
list the frequent \(k\)-itemset for the largest \(k\) (but do not print any rules).

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Data Mining Concepts And Techniques

ISBN: 9780128117613

4th Edition

Authors: Jiawei Han, Jian Pei, Hanghang Tong

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