I have a number of time series (different lengths, different amplitudes) that I want to cluster according their similarity. Does anyone know about any method for normalizing DTW scores to make the scores comparable between them? Thanks.
I transform raw scores to normal quantiles befire doing a cluster analysis. In SAS it is given under proc rank. I use the BLOM method for ranking. Van der Waerden started this type of transformations. The text by Conover explains it too.
There also a soft-DTW version similar to a kernel. This gives you values between 0 and 1 like a softmax output. It can be found in the tslearn library (Python).