# Column generation based math-heuristic for classification trees

arXiv: https://arxiv.org/abs/1810.06684 · HTML: https://mlsanity.com/paper/1810.06684/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Oct 2018.

## Built on by (most cited first, 1 of 1)

- [Dive into Decision Trees and Forests: A Theoretical Demonstration](https://mlsanity.com/paper/2101.08656/) (2021)

## Abstract (arXiv)

This paper explores the use of Column Generation (CG) techniques in constructing univariate binary decision trees for classification tasks. We propose a novel Integer Linear Programming (ILP) formulation, based on root-to-leaf paths in decision trees. The model is solved via a Column Generation based heuristic. To speed up the heuristic, we use a restricted instance data by considering a subset of decision splits, sampled from the solutions of the well-known CART algorithm. Extensive numerical experiments show that our approach is competitive with the state-of-the-art ILP-based algorithms. In particular, the proposed approach is capable of handling big data sets with tens of thousands of data rows. Moreover, for large data sets, it finds solutions competitive to CART.