Article
Version 1
Preserved in Portico This version is not peer-reviewed
Machine Learning Models for Sales Time Series Forecasting
Version 1
: Received: 3 November 2018 / Approved: 5 November 2018 / Online: 5 November 2018 (09:54:54 CET)
A peer-reviewed article of this Preprint also exists.
Pavlyshenko, B.M. Machine-Learning Models for Sales Time Series Forecasting. Data 2019, 4, 15. Pavlyshenko, B.M. Machine-Learning Models for Sales Time Series Forecasting. Data 2019, 4, 15.
Abstract
In this paper, we study the usage of machine learning models for sales time series forecasting. The effect of machine learning generalization has been considered. A stacking approach for building regression ensemble of single models has been studied. The results show that using stacking technics, we can improve the performance of predictive models for sales time series forecasting.
Keywords
machine learning; stacking; forecasting; regression; sales; time series
Subject
Computer Science and Mathematics, Information Systems
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
