I've been recently studying DBSCAN with R for transit research purposes, and I'm hoping if someone could help me with this particular dataset.
Summary of my dataset is described below.
BTIME ATIME
1029 20001 21249
2944 24832 25687
6876 25231 26179
11120 20364 21259
11428 25550 26398
12447 24208 25172
What I am trying to do is to cluster these data using BTIME as x axis, ATIME as y axis. A pair of BTIME and ATIME represents the boarding time and arrival time of a subway passenger.
For more explanation, I will add the scatter plot of my total data set.
However if I split my dataset in different smaller time periods, the scatter plot looks like this. I would call this a sample dataset.
If I perform a DBSCAN clustering on the second image(sample data set), the clustering is performed as expected.
However it seems that DBSCAN cannot perform cluster on the total dataset with smaller scales. Maybe because the data is too dense.
So my question is, Is there a way I can perform clustering in the total dataset? What criteria should be used to separate the time scale of the data
I think the total data set is highly dense, which was why I tried clustering on a sample time period.
If I seperate my total data into smaller time scale, how would I choose the hyperparameters for each seperated dataset? If I look at the data, the distribution of the data is similar both in the total dataset and the seperated sample dataset.
I would sincerely appreciate some advices.