Make a prediction using Actor-Critic shared model from timeseries data using Python

Asked Oct 14 '22 at 12:43

Active Oct 14 '22 at 12:43

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I have been able to train and test a shared RL model that produces a Actor.h5 and Critic.h5 file, as well as a json containing the parameters for training.

I am now at the stage where I would like to make a prediction on the next best action for the model to take, based on the 50 previous time series data points. One was I have been doing this is to use a modified version of my test function and reducing the data frame a little larger than my 50 lookback window, then taking the final prediction/action in the episode of testing.

I think this is a work around and was looking for some advice on the methodology to approach this.

Thanks.

asked Oct 14 '22 at 12:43

Ben Wilson

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking. – Community Oct 14 '22 at 14:29

Make a prediction using Actor-Critic shared model from timeseries data using Python

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