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How to calculate features for forecasted time frame RRS feed

  • Question

  • Hello,

    I have a question about how to calculate features for forecasted time frames. Some experiment examples on azure talk about foresting sales for retail stores, but they do not provided guidelines to predict the features' feature values. To get in more details, consider the below dataset and consider today is: 2019-11-11. I have last 2 years of daily data and below is last 6 rows:

    Date, Temperature, Sales

    2019-11-06, 25.5, 500000

    2019-11-07, 24.2, 550000

    2019-11-08, 25.1, 560000

    2019-11-09, 22.6, 510000

    2019-11-10, 22.3, 520000

    2019-11-11, 24.4, 535000

    ------- Now I have to predict Sales for 2019-11-12, 2019-11-13, 2019-11-14. In order to predict sales for those dates, I have to provide below test data to the machine learning trained model:

    Date, Temperature

    2019-11-12, temperatureX

    2019-11-13, temperatureY

    2019-11-14, temperatureZ

    -- What will be values for temperatureX, temperatureY and temperatureZ since these values will be coming from future as well ?

    Regards.

    Alejandro.

    Monday, November 11, 2019 10:38 AM

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