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The gap between a model that achieves a respectable validation metric and a model that produces decisions a business can act on is almost always found in the features — in whether the inputs to the model actually encode the information the model needs to separate the signal it is looking for from the noise it needs to ignore."}],["$","p","1",{"className":"text-base text-foreground leading-[1.85] font-medium","children":"Lag features are the most important class of features for any prediction problem with a temporal dimension, and they are the features that are most often missed by teams that approach machine learning from a purely statistical background rather than a domain knowledge background. A demand forecast that includes yesterday's sales, the sales from the same day last week, and the sales from the same day last year is operating on information that is directly relevant to today's prediction. 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