Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Augmented Data and XGBoost Improvement for Sales Forecasting in the Large-Scale Retail Sector

13 references·2 citing·44 second hop

FromToDepth

this work references cited by second hop

References

2006Competing on analytics.994 cited
2004The accuracy of intermittent demand estimates498 cited
2013A Survey of Forecast Error Measures463 cited
1994Artificial neural network models for forecasting and decision making450 cited
2019Machine-Learning Models for Sales Time Series Forecasting245 cited
2017Crude oil price forecasting using XGBoost168 cited
1998A decision support system for sales forecasting through fuzzy neural networks with asymmetric fuzzy weights121 cited
2019An Application of a Three‐Stage XGBoost‐Based Model to Sales Forecasting of a Cross‐Border E‐Commerce Enterprise93 cited
2020Machine learning-based e-commerce platform repurchase customer prediction model70 cited
2018Sales-forecasting of Retail Stores using Machine Learning Techniques60 cited
2019Business Intelligence Improved by Data Mining Algorithms and Big Data Systems: An Overview of Different Tools Applied in Industrial Research36 cited
2020An XGBoost Algorithm for Predicting Purchasing Behaviour on E-Commerce Platforms33 cited
2017An accident prediction approach based on XGBoost32 cited

Cited by

2024Systematic Mapping Study of Sales Forecasting: Methods, Trends, and Future Directions33 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

2025Data Driven Retail Price Optimization using XGBoost and Predictive Modeling9 cited