A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque
Data Structures and Algorithms
2017-12-22 v2
Abstract
This short article presents a new implementation for decision trees. By introducing pre-sorted deques, the leaf-wise greedy tree growing strategy no longer needs to re-sort data at each node, and takes O(kn) time and O(1) extra memory locating the best split and branching. The consistent, superior performance - plus its simplicity and guarantee in producing the same classification results as the standard decision trees - makes the new implementation a drop-in replacement for depth-wise tree induction with strong performance.
Keywords
Cite
@article{arxiv.1712.06989,
title = {A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque},
author = {Jianbo Ye},
journal= {arXiv preprint arXiv:1712.06989},
year = {2017}
}
Comments
4 pages, updated with new statistics and fix typos