Generic Itemset Mining Based on Reinforcement Learning. (arXiv:2105.07753v2 [cs.DB] UPDATED)

One of the biggest problems in itemset mining is the requirement of
developing a data structure or algorithm, every time a user wants to extract a
different type of itemsets. To overcome this, we propose a method, called
Generic Itemset Mining based on Reinforcement Learning (GIM-RL), that offers a
unified framework to train an agent for extracting any type of itemsets. In
GIM-RL, the environment formulates iterative steps of extracting a target type
of itemsets from a dataset. At each …

arxiv learning mining reinforcement learning