Unsupervised classification of objects based on relationships I have size measurements of 1000 objects, measured over time. I would like to classify the objects based on the response of their size to time using unsupervised classification.
For example, the size of the object can follow one of the below 6 different curves.

I used k-proto from library(clustMixType) for unsupervised classification giving the object's ID as a factor variable. However, the classification was performed on individual time measurements instead of objects.
Is there any way to classify the objects based on the size-time relationship?

I would start by trying to calculate a set of statistics that would differentiate all these curve types.
Some examples of statistics could be: mean, std, min, max, gradient mean/std, number of positive/negative turning points (note these should be specifically chosen to separate out the expected curve types).
Then using your statistics as a model input you would try to cluster the results. After which, you would investigate the clusters to check that all the curves are similar (e.g., check the MSE of each curve to the average for the cluster etc.).
