Comments (4)
If all your trajectories have the same length then you would just create a matrix where each row has all the x and y values of the points defining the trajectory.
from dbscan.
Thank you! Let me ask you additional questions:
- Is it the same to treat the data as {(x1, y1), (x2, y2) ..., (xn, yn)} and as (x1, x2, ..., xn, y1, y2, ..., yn) in the context of DBSCAN? Your answer is the latter case, but I'm not sure if they are identical.
- What if I would like to analyze trajectories with different lengths? Does a matrix with NA work? (e.g. trajectory 1: length 5, trajectory 2: length 3 -> Can I fill the tail of the row of trajectory 2 with NA?)
from dbscan.
Different lengths are an issue and NAs will not work. The best solution would be to calculate a distance matrix between the trajectories using the appropriate approach (see e.g., https://zheng-kai.com/paper/vldbj_2019.pdf) and then do dbscan on that distance matrix.
from dbscan.
Thank you very much. I will look over the paper!
from dbscan.
Related Issues (20)
- NA values on parameters in dbscan HOT 1
- hdbscan, distance matrix HOT 3
- Segmentation fault in HDBSCAN when clustering a large(?) dataset HOT 1
- some strange results of sNN function HOT 7
- Discrepancies in outlier score between HDBSCAN R and python HOT 7
- Implement Density-Based Clustering Validation (DBCV) HOT 2
- BD-trees
- DBSCAN with categorica/factor/dummy variables HOT 1
- hdbscan HOT 2
- LOF edge case HOT 2
- LOF fails after upgrading to dbscan 1.1-6 HOT 2
- Possible Memory Leak HOT 2
- kNN crashing (segfault) when matrix has Inf values HOT 1
- mrdist error in large datasets HOT 3
- frNN object created from scratch couldn't be used in dbscan HOT 6
- Error in mrd(x_dist, coredist) : number of mutual reachability distance values and size of the distances do not agree. HOT 6
- Getting an error when using predict: x has to be a numeric matrix. HOT 2
- may you clarify is multi-density clustering is implemented, since it is mentioned on references ? HOT 1
- R session aborted in pointdensity() HOT 4
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from dbscan.