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Selecting an appropriate model to forecast product demand is critical to themanufacturing industry. However, due to the data complexity, market uncertaintyand users' demanding requirements for the model, it is challenging for demandanalysts to select a proper model. Although existing model selection methodscan reduce the manual burden to some extent, they often fail to present modelperformance details on individual products and reveal the potential risk of theselected model. This paper presents DFSeer, an interactive visualization systemto conduct reliable model selection for demand forecasting based on theproducts with similar historical demand. It supports model comparison andselection with different levels of details. Besides, it shows the difference inmodel performance on similar products to reveal the risk of model selection andincrease users' confidence in choosing a forecasting model. Two case studiesand interviews with domain experts demonstrate the effectiveness and usabilityof DFSeer.

DFSeer: A Visual Analytics Approach to Facilitate Model Selection for Demand Forecasting