I have data which contains access duration of some items.
t0~t5 is the access time duration, 1 means the items was accessed in the time duration, 0 means it wasn't.
ID,t0,t1,t2,t3,t4 0,0,0,1,1,1 1,0,1,1,1,1 2,0,1,1,0,0 3,1,1,0,0,1 4,1,1,0,0,1
In the above example, groups
ID=0,1 are what I want.
ID=3,4 aren't because their distance is short but they are not continuous.
DBSCAN, they all cluster
ID=3,4 as one group and it makes sense. But it doesn't do what I want.
Is there any possible pre-processing of data to reach what I want ?
Or I should use other analytic tool?