An incremental mining algorithm for erasable itemsets
Tzung‐Pei Hong, Kun‐Yi Andrew Lin, Chun-Wei Lin, Bay Vo · 2017
Erasable-itemset (EI) mining is to find the itemsets that can be eliminated but do not greatly affect the factory's profit. In this paper, an incremental mining algorithm for erasable itemset is proposed. It is based on the concept of the fast-update (FUP) approach, which was originally designed for association mining. Experimental results show that the proposed algorithm executes faster than the batch approach in the intermittent data environment.