Document Type
Article
Publication Date
5-30-2023
Abstract
Purpose: This paper aims to examine how the regional variable in country conflict modeling affects forecast accuracy and identifies a methodology to further improve the predictions.
Design/methodology/approach: This paper uses statistical learning methods to both evaluate the quantity of data for clustering countries along with quantifying accuracy according to the number of clusters used.
Findings: This study demonstrates that increasing the number of clusters for modeling improves the ability to predict conflict as long as the models are robust.
Originality/value: This study investigates the quantity of clusters used in conflict modeling, while previous research assumes a specific quantity before modeling.
Source Publication
Journal of Defense Analytics and Logistics
Recommended Citation
Leiby, B. and Ahner, D. (2023), "A hierarchical cluster approach toward understanding the regional variable in country conflict modeling", Journal of Defense Analytics and Logistics, Vol. 7 No. 1, pp. 48-68. https://doi-org.afit.idm.oclc.org/10.1108/JDAL-11-2022-0011
Comments
All articles published in JDAL are published Open Access under a Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CC BY 4.0
Sourced from the publisher version of record at Emerald. The citation and DOI link are noted below.