In this paper, we address the challenges that arise from this problem by providing a novel approach to restructure and prune Hoeffding trees. We evaluate our approach on synthetic datasets, where we can show that the approach significantly improves the performance compared to the baseline of an adjusted Hoeffding tree algorithm without restructuring and pruning.
Restructuring of Hoeffding Trees for Trapezoidal Data Streams
Credit: Christian Schreckenberger, Tim Glockner