Machine-learning models for sales time series forecasting

144Citations
Citations of this article
633Readers
Mendeley users who have this article in their library.

Abstract

In this paper, we study the usage of machine-learning models for sales predictive analytics. The main goal of this paper is to consider main approaches and case studies of using machine learning for sales forecasting. The effect of machine-learning generalization has been considered. This effect can be used to make sales predictions when there is a small amount of historical data for specific sales time series in the case when a new product or store is launched. A stacking approach for building regression ensemble of single models has been studied. The results show that using stacking techniques, we can improve the performance of predictive models for sales time series forecasting.

Cite

CITATION STYLE

APA

Pavlyshenko, B. M. (2019). Machine-learning models for sales time series forecasting. Data, 4(1). https://doi.org/10.3390/data4010015

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free