The main objective of the M5 competition, which focused on forecasting the hierarchical unit sales of Walmart, was to evaluate the accuracy and uncertainty of forecasting methods in the field in order to identify best practices and highlight their practical implications. However, whether the findings of the M5 competition can be generalized and exploited by retail firms to better support their decisions and operation depends on the extent to which the M5 data is representative of the reality, i.e., sufficiently represent the unit sales data of retailers that operate in different regions, sell different types of products, and consider different marketing strategies. To answer this question, we analyze the characteristics of the M5 time series and compare them with those of two grocery retailers, namely Corporaci\'on Favorita and a major Greek supermarket chain, using feature spaces. Our results suggest that there are only small discrepancies between the examined data sets, supporting the representativeness of the M5 data.

中文翻译：

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探索M5竞赛数据的代表性

M5竞赛的主要目标是预测沃尔玛的分层单位销售额，目的是评估该领域预测方法的准确性和不确定性，以便确定最佳实践并突出其实际意义。但是，M5竞争的结果是否可以被零售公司推广和利用，以更好地支持其决策和运营取决于M5数据代表现实的程度，即足以代表零售商的单位销售数据，在不同地区运营，销售不同类型的产品，并考虑不同的营销策略。为了回答这个问题，我们分析了M5时间序列的特征，并将其与两家杂货店零售商Corporaci''的特征进行了比较。在Favorita和希腊主要的连锁超市上使用功能空间。我们的结果表明，所检查的数据集之间只有很小的差异，这支持了M5数据的代表性。