Multivariate Time Series Analysis with an RNN - Training

This is a simple example workflow for multivariant time series analysis using an LSTM based recurrent neural network and implemented via the KNIME Deep Learning - Keras Integration. It is based on the bike demand predition dataset from Kaggle and trains a model to predict the demand in the next hour based on the demand and the other features in the last 10 hours.

This is a companion discussion topic for the original entry at


I downloaded this workflow to give it a try since am working on a similar project.However,to my dismay I ran some node successfully but I can’t progress past keras network learner.Nothing seems to be happening here for an entire night.

Below is a screen shot of it and see attached is the console output.

I am working on windows 10.I have also installed all the extensions and I tested another Keras workflow which worked fine(see below)


See also attached ananconda dependecies.Anaconda dependencies.txt (6.8 KB) Console output.txt (1.2 KB)

Please let me know what the problem could be the problem

I haven’t finished running this workflow yet myself, but I wanted to note that you can check the progress of the Keras Network Learner by right-clicking on it while it executes and selecting “View: Learning Monitor”. On my machine (no GPU) it’s taking about 40 seconds per epoch, so this should still finish in under an hour.

Can you check this post to see if the suggestions help you? KNIME 4.1: Keras error ( Selected Keras backend 'Keras(Tensorflow)' is not available anymore - #14 by MarcelW


I tried recreating the workflow with the knime versions and extensions originally used to develop the workflow but there is no progress.

See below and attached log files and anaconda environment created and all packages associated with it.

There is a big problem somewhere. Does this mean the problem only works on certain OS?
Please let me know what the problem could be.Conda trouble shooting.txt (12.4 KB) Console output.txt (1.2 KB)