Food Sales Prediction: "If Only It Knew What We Know"
ICDMW '08 Proceedings of the 2008 IEEE International Conference on Data Mining Workshops
Beating the baseline prediction in food sales: How intelligent an intelligent predictor is?
Expert Systems with Applications: An International Journal
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Sales prediction is an important problem for different companies involved in manufacturing, logistics, marketing, wholesaling and retailing. Different approaches have been suggested for food sales forecasting. Several researchers, including the authors of this paper, reported on the advantage of one type of technique over the others for a particular set of products. In this paper we demonstrate that besides an already recognized challenge of building accurate predictive models, the evaluation procedures themselves should be considered more carefully. We give illustrative examples to show that e.g. popular MAE and MSE estimates can be intuitive with one type of product and rather misleading with the others. Furthermore, averaging errors across differently behaving products can be also counter intuitive. We introduce new ways to evaluate the performance of wholesales prediction and discuss their biases with respect to different error types.