chapter8

Itemset mining

Frequent Itemsets and accosiation rules

  • \(I \subseteq \mathcal{I} = \{x_1, x_2,..., x_m\}\) (itemset)
  • \(T \subseteq \mathcal{T} = \{t_1, t_2, ..., t_m\}\) (tidset)
  • \((t, X)\) transaction (itenditfier t)

Database Representation

  • D is a binary relation on the set of tids and items
  • \(2^\mathcal I\) power set (all possible subsets)

Support and frequent subsets

Itemset mining algorithms

Candidate generation

Support computation

Level wise approach apriori algorithm