Abstract
In this chapter, we summarize all the results obtained so far and compare the different methods in terms of prediction accuracy. We then present several simple ways to visualize and communicate the prediction results. Finally, we consider varying the ratio of the train-test data split to assess the robustness of our results.
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The clustering procedure is based on the average values and standard deviations of the price and weekly sales.
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Cohen, M.C., Gras, PE., Pentecoste, A., Zhang, R. (2022). Evaluation and Visualization. In: Demand Prediction in Retail . Springer Series in Supply Chain Management, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-030-85855-1_6
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DOI: https://doi.org/10.1007/978-3-030-85855-1_6
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Publisher Name: Springer, Cham
Print ISBN: 978-3-030-85854-4
Online ISBN: 978-3-030-85855-1
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