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Time series model with missing week end

Abhishek Saha
Blue LED

Hi,

 

In our time series problem we are having the dataset that contains the data only for week days.

 

So, in our case, if we are presently at on Wednesday.....

 

1 day future value means Thursday.

2 day future value means Friday.

3 day future value means Monday (not saturday)

4 day future value means Tuesday (Not Sunday).

 

But while working with time series problem, DataRobot can't exclude the week ends. So, if we provide the forecast window 1-40 days. Then practically we receive the forecasting of next 28 week days (because remaining 2X6=12 are weekends). But we need the forecasting for next 40 week days.

 

What should be the solution? Thanks for the help for your advice.

 

Thanks and Regards

Abhishek Saha

 

 

1 Reply
JessLin
Data Scientist
Data Scientist

Hi Abhishek,

 

There are a couple different ways you can handle this!

 

1) Switch time series to "row-based" mode, and set the forecast window to [1,40], and make sure that your prediction dataset only contains weekdays

Screen Shot 2021-05-07 at 10.56.10 AM.png
(screenshot of how to set up the time series settings)

Pros: The "forecast distance" matches up to future # weekdays (eg "1 row ahead" will always equate to "1 weekday ahead" regardless of weekends)

Cons: you lose any date-related feature engineering (eg "week aggregation")

 

2) Stay in "day-based" mode, but increase the forecast window to [1,56]

Screen Shot 2021-05-07 at 11.14.37 AM.png

(screenshot of what the output would look like - notice the missing weekends)

Pros: Keep date-related feature engineering, and you'll still forecast the next 40 week days

Cons: Your forecast distance doesn't precisely match up to future # of weekdays (depending on your forecast point, "forecast distance = 3" may mean 3 days ahead, or it may mean the next weekday)

 

Hope this helps!

- Jess