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Gradient Boosting Application in Forecasting of Performance Indicators Values for Measuring the Efficiency of Promotions in FMCG Retail

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arxiv 2006.04945 v1 pith:A6JGHAG3 submitted 2020-05-30 cs.CY cs.LGstat.ML

classification cs.CYcs.LGstat.ML
keywords efficiencyforecastingpromotionboostinggradientgroupsindicatorsperformance
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In the paper, a problem of forecasting promotion efficiency is raised. The authors propose a new approach, using the gradient boosting method for this task. Six performance indicators are introduced to capture the promotion effect. For each of them, within predefined groups of products, a model was trained. A description of using these models for forecasting and optimising promotion efficiency is provided. Data preparation and hyperparameters tuning processes are also described. The experiments were performed for three groups of products from a large grocery company.

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