Knime is a very powerful machine learning tool, particularly suitable for the management of complicated workflows as well as rapid prototyping.
It has recently become yet more useful with the arrival of easy-to-use Python nodes. This is true because sometimes the set of nodes – which is large – still may not provide the exact functionality that you need. On the other hand, Python is flexible enough to do anything easily. Therefore the marriage of the two is very powerful.
This post is about the transfer of the three previous time series prediction posts into a knime workflow.
This will provide for a good overview of the dataflow, making it thus more easily manageable.
The workflow code is available on github:
Continue reading “Knime – Multivariate time series”