English

State-of-the-art predictive and prescriptive analytics for IEEE CIS 3rd Technical Challenge

Machine Learning 2021-12-08 v1

Abstract

In this paper, we describe our proposed methodology to approach the predict+optimise challenge introduced in the IEEE CIS 3rd Technical Challenge. The predictive model employs an ensemble of LightGBM models and the prescriptive analysis employs mathematical optimisation to efficiently prescribe solutions that minimise the average cost over multiple scenarios. Our solutions ranked 1st in the optimisation and 2nd in the prediction challenge of the competition.

Keywords

Cite

@article{arxiv.2112.03595,
  title  = {State-of-the-art predictive and prescriptive analytics for IEEE CIS 3rd Technical Challenge},
  author = {Mahdi Abolghasemi and Rasul Esmaeilbeigi},
  journal= {arXiv preprint arXiv:2112.03595},
  year   = {2021}
}
R2 v1 2026-06-24T08:07:18.470Z