I'm an ELKI beginner, and I've been using it to cluster around 10K lat-lon points from a .csv file. Once I get my settings correct, I'd like to scale up to 1MM points.
I'm using the OPTICSXi algorithm with LngLatDistanceFunction
I keep reading about "enabling R*-tree index with STR bulk loading" in order to see vast improvements in performance. The tutorials haven't helped me much.
Any tips on how I can implement this feature?
The suggested parameters for using a spatial R* index on 2 dimensional data are:
-db.index tree.spatial.rstarvariants.rstar.RStarTreeFactory
-pagefile.pagesize 512
-spatial.bulkstrategy SortTileRecursiveBulkSplit
For higher dimensional data, larger page sizes are necessary. A page size of 512-1024 bytes seems to be the sweet spot for 2 dimensional data, but it does depend on your data, too.
To discretize clusters, you can use the Xi extraction:
-algorithm clustering.optics.OPTICSXi -opticsxi.xi 0.005
To benefit from index acceleration with OPTICS, choose epsilon as small as possible for your application. The parameter is in meters with all the earth models in ELKI.
-opticsxi.algorithm OPTICSHeap
-algorithm.distancefunction geo.LatLngDistanceFunction
-optics.epsilon 2000.0 -optics.minpts 10
uses 2 km distances maximum.
Make sure to distinguish latitude,longitude and longitude,latitude. Both orders are used, and you need to use the right distance function:
geo.LatLngDistanceFunction
geo.LngLatDistanceFunction
