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I'm studying machine learning (e.i. time series analysis). I encountered an Azure tutorial, Retail Forecasting.

https://gallery.azure.ai/Experiment/Retail-Forecasting-Step-2-of-6-train-time-series-models-3

Here, they introduce new features called "lag", which I don't understand what it means. In 3.4, they said "The module selects the best lag of this index based on maximum correlation." What does it mean? Could you please let me know some references to learn background knowledge?

When you have a variable which is dependent on time $x_t$, the first lag of $x$ is $x_{t-1}. So you look back in time. The idea is that in many cases, previous outcomes are dependent on "yesterdays" outcome. E.g. todays temperature is correlated to yesterdays temperature. – Peter – 2020-04-17T11:55:09.117

Thank you for your response. Could you also explain what "the best lag" means? – hgshin – 2020-04-17T12:05:33.193

You can choose lags $x_{t-1}$,$x_{t-2}$ up to $x_{t-n}$ and you don't know ex ante what lag(s) to choose. The best lag cold be ont with most power to explain some outcome. – Peter – 2020-04-17T12:11:39.580