I have database of sequential events for multiple animals. The events are represented by integers so it looks something like:

Animal A: [1,6,4,2,5,7,8] 
Animal B: [1,6,5,4,1,6,7]
Animal C: [5,4,2,1,6,4,3]

I can manually see that for each event 6 event 1 first happens. And event 4 happens quickly after a 1,6 combination. But these are easy to spot in such a small dataset, the real lists are 10000+ events per animal. Is there a way to use an algorithm or machine learning to search for these kinds of patterns?

  • $\begingroup$ So, you do not know in advance how many patterns a sequence may have and the type of patterns, right? $\endgroup$ – nbro Nov 16 '20 at 11:42
  • $\begingroup$ @nbro I do not no. I could manually search for patterns but I want to also find some deeper hidden patterns which may not be obvious $\endgroup$ – Bram Nov 16 '20 at 13:05

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