I would like to classify a relatively large set (over 9000) of short times series. The length of each sequence varies, but I would say about 80 % has between 2 and 9 observations. While I could use a simple trendline (maybe combined with a variance measure) to describe each these sequences, I would like to go a step beyond this solution.
What other kinds of methods could I utilize to cluster the "visual appearance" of these sequences? The ultimate goal of the classification is to gain a understanding of what type of trend/style/behavior each sequence is exhibiting.