CODEWITHSUNDEEP
pythontensorflowtime-series
marcin
marcin

Reputation: 567

How to add future feature data to STS model - TensorFlow

I went through this case study of Structural Time Series Modeling in TensorFlow, but I couldn't find a way to add future values of features. I would like to add holidays effect, but when I am following these steps my holidays starts to repeat in forecast period.

Below is visualisation from case study, you can see that temperature_effect starts from begginig.

enter image description here

Is it possible to feed the model with actual future data?

Edit: In my case holidays started to repeat in my forecast which does not make sense. Just now I have found issue on github refering to this problem, there is workaround to this problem. enter image description here

Upvotes: 0

Views: 322

Answers (2)

Jason Chia
Jason Chia

Reputation: 1145

There is a slight fallacy in what you are asking in particular. As mentioned in my comment when predicting with a model, future data does not exist because it just hasn't happened yet. For whatever model its not possible to feed data that does not exist. However you could use an autoregressive approach as defined in the link above to feed 'future' data. A Pseudo example would be as follows:

Model 1: STS model with inputs x_in and x_future to predict y_future.

You could stack this with a secondary helper model that predicts x_future from x_in.

Model 2: Regression model with input x_in predicting x_future.

Concatenating these models will result then allow your STS model to take into account 'future' feature elements. On the other hand in your question you mention a holiday effect. You could simply add another input where you define via some if/else case if a holiday effect is active or inactive. You could also use random sampling of your holiday effect as well and it might help. To exactly help you with code/model to do what you want I'll need to have more details on your model/inputs/outputs.

In simple words, you can't work with data that doesn't exist so you either need to spoof it or get it in some other way.

Upvotes: 1

lazy
lazy

Reputation: 784

The tutorial on forecasting is here：https://www.tensorflow.org/probability/examples/Structural_Time_Series_Modeling_Case_Studies_Atmospheric_CO2_and_Electricity_Demand

You only need to enter new data and parameters to predict how many results in the future.

Upvotes: 0

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