MARKET BASKET ANALYSIS AND CLUSTERING

You have been provided with a dataset containing transaction records from an online retail store. Use this dataset to perform the following tasks:. The pattern of purchase has to be found out for a minimum support of $2$

$\backslash$table$[[$T$1$D$,$ITEMSETS$],[$T$1,$A$,$ B$],[$T$2,$B$,$ D$],[$T$3,$B$,$ C$],[$T$4,$A$,$ B$,$ D$],[$T$5,$A$,$ C$],[$T$6,$B$,$ C$],[$T$7,$A$,$ C$],[$T$8,$A$,$ B$,$ C$,$ E$],[$T$9,$A$,$ B$,$ C$]]$

Given: Minimum Support $=2,$ Minimum Confidence $=50\%$

a$.$ Apply the Apriori algorithm to identify frequent itemset with a minimum support of $2.(10$ marks$)$

$($Marking Scheme: $2$ marks finding the algorithm to be used $+2$ marks for applying support count of each item $+2$ marks for finding reduced dataset $+2$ marks for finding number of joining and pruning $+2$ marks for correct final answer$)$

b$.$ Build the FP Tree and mine frequent patterns$(10$marks$)$

$($Marking Scheme: $2$ marks for initial dataset with support counts $+2$ marks for the reduced dataset $+2$ marks for the ordered dataset $+2$ marks for the final tree $+2$ marks for following correct patterns in the tree$)$

c$.$ Discuss potential marketing strategies based on the discovered patterns. $(5$marks$)$