I have some data in following format:
kid1, 6am, sleeping kid1, 7am, sleeping kid1, 8am, sleeping kid1, 9am, playing kid1, 10am, playing kid1, 11am, eating kid2, 6am, sleeping kid2, 7am, sleeping kid2, 8am, sleeping kid2, 9am, playing kid2, 10am, playing kid2, 11am, eating
We can easily spot the pattern here that kid1 slept for 3 hours, played for 2 hours etc.
Same thing I want to do using machine learning. Some people suggested using decision trees, graphs etc etc. However, it is not a labeled data and the activities like sleeping, eating can also be in some good number. Thought of unsupervised clustering and time series too, but couldn't get it working.
Can someone suggest an actual working example (if some similar code is there, I can tweak).
I believe this is an old problem of data science, just a right hint if someone can give, that would be helpful.