Theoretical Analysis of an XGBoost Framework for Product Cannibalization
Machine Learning
2021-12-06 v1
Abstract
This paper is an extension of our work where we presented a three-stage XGBoost algorithm for forecasting sales under product cannibalization scenario. Previously we developed the model based on our intuition and provided empirical evidence on its performance. In this study we would briefly go over the algorithm and then provide mathematical reasoning behind its working.
Keywords
Cite
@article{arxiv.2112.01566,
title = {Theoretical Analysis of an XGBoost Framework for Product Cannibalization},
author = {Gautham Bekal and Mohammad Bari},
journal= {arXiv preprint arXiv:2112.01566},
year = {2021}
}
Comments
To better understand this paper please go through the previous paper, An XGBoost-Based Forecasting Framework for Product Cannibalization. This paper is an extension of the previous work