I have a model based on LSTMs that can predict a vector output based on a vector input. I can't increase the size of the output because :
- I would need a larger network to obtain good results
- It would take more time to train
- The behaviour of my timeseries can be captured in the size of the vector I'm already predicting
So I tried to predict an output, and then use that prediction as a new input in my model and predict a new vector (without re-training). I iterate 5 times and I get this result :
As you can see, the first prediction is pretty good. Then, my model is lost and loses its accuracy. Do you know how to fix it ?