Detail práce

Machine learning-based approaches to forecasting international trade

Autor: Bc. Tomáš Kovařík
Rok: 2019 - zimní
Vedoucí: Ing. Vilém Semerák M.A., Ph.D.
Konzultant:
Typ práce: Bakalářská
Jazyk: Anglicky
Stránky: 44
Ocenění:
Odkaz: https://is.cuni.cz/webapps/zzp/detail/191197/
Abstrakt: In this thesis I focus on comparison of gravity model estimated with ordinary
least squares and Poisson pseudo-maximum likelihood with regression techniques
based on machine learning, namely support vector machines, random
forests, and arti_cial neural networks. I discuss the advantages and disadvantages
of these approaches and compare their forecasting accuracy on
exports data. I demonstrate that random forest models and arti_cial neural
networks provide superior forecasting accuracy

Partneři

Deloitte
McKinsey & Company
Moneta Money Bank

Sponzoři

CRIF
ČSOB