Automating DBSCAN via Deep Reinforcement Learning. (arXiv:2208.04537v1 [cs.LG])

DBSCAN is widely used in many scientific and engineering fields because of
its simplicity and practicality. However, due to its high sensitivity
parameters, the accuracy of the clustering result depends heavily on practical
experience. In this paper, we first propose a novel Deep Reinforcement Learning
guided automatic DBSCAN parameters search framework, namely DRL-DBSCAN. The
framework models the process of adjusting the parameter search direction by
perceiving the clustering environment as a Markov decision process, which aims
to find the best …

arxiv dbscan learning lg reinforcement reinforcement learning