Machine-Learning Models for Sales Time Series Forecasting

摘要

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 learningfor sales forecasting. The effect of machine-learning generalization has been considered. This effectcan be used to make sales predictions when there is a small amount of historical data for specificsales time series in the case when a new product or store is launched. A stacking approach forbuilding regression ensemble of single models has been studied. The results show that using stackingtechniques, we can improve the performance of predictive models for sales time series forecasting.