Optimal binning: mathematical programming formulation
Machine Learning
2022-12-12 v3 Optimization and Control
Machine Learning
Abstract
The optimal binning is the optimal discretization of a variable into bins given a discrete or continuous numeric target. We present a rigorous and extensible mathematical programming formulation for solving the optimal binning problem for a binary, continuous and multi-class target type, incorporating constraints not previously addressed. For all three target types, we introduce a convex mixed-integer programming formulation. Several algorithmic enhancements, such as automatic determination of the most suitable monotonic trend via a Machine-Learning-based classifier and implementation aspects are thoughtfully discussed. The new mathematical programming formulations are carefully implemented in the open-source python library OptBinning.
Cite
@article{arxiv.2001.08025,
title = {Optimal binning: mathematical programming formulation},
author = {Guillermo Navas-Palencia},
journal= {arXiv preprint arXiv:2001.08025},
year = {2022}
}