Prediction with Deep Learning / LSTM
So far, I have done time series forecasting (e.g., stock value forecasting) using autoregression ARIMA, using the operators Retrieve--Filter Examples--ARIMA--Apply Forecast.
Since the extensions for LSTM layers are now available, I wanted to try the time series forecasts with Deep Learning.
To do this, I simply replaced the ARIMA operator with the Deep Learning operator [Extension]. Similarly, I replaced Apply Forecast with Apply Model (Generic) [Extension].
For the inner structure of the Deep Learning operator I
chose the following sequence:
Add Fully-Connected Layer with neurons = 1 and activation function = ReLU; Add LSTM Layer with neurons = 10 and activation function = ReLU; Add Output Layer with output type = Automatic.
Unfortunately, this simple model does not work and gives the error message "Network configuration problem".
I would be extremely grateful to the experts here if you could give me some helpful tips?Regards Torsten