We do have a data set with several data points per case where the number of data points per case differ. These data points are ordered intime. We want to make sure that each case has the same influence on the predictions in the end and thus not every data point can have the same influence. Therefore we are considering time warping of the data points. However, we do not know how to model this in KNIME. Is this possible? And what nodes should we use?
Thanks in advance!
Welcome to KNIME community forum and sry for a delay on this one.
As to my knowledge KNIME doesn’t have dedicated nodes for Time Wrapping if we are thinking the same. However KNIME does have both R and Python integrations which have DWT libraries so check that options
Additionally I’m not aware what kind of predictions are you making and what kind of data set you got but not sure how would you use time wrapping so that every data point has same influence. If you share a bit more maybe you will get some suggestions/ideas.
Have a nice day,