DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm
Alexandre Termier, M.-C. Rousset, Michèle Sébag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda · IEEE Transactions on Knowledge and Data Engineering · 2008
In this paper, we present a new tree mining algorithm, DryadeParent, based on the hooking principle first introduced in DRYADE. In the experiments, we demonstrate that the branching factor and depth of the frequent patterns to find are key factors of complexity for tree mining algorithms, even if often overlooked in previous work. We show that DryadeParent outperforms the current fastest algorithm, CMTreeMiner, by orders of magnitude on data sets where the frequent tree patterns have a high branching factor.