We have boring CSV with 10000 rows of
ages (float), titles (enum/int), scores (float). How to select 1000 most different rows? I look for a general solution that would work for more than one case.
What do I mean by different:
- We have N columns each with int/float values in a table.
- You can imagine this as points in ND space
- We want to pick K points that would have maximised distance between each other.
It looks like an ND point cloud "triangulation" with a given resolution yet not for 3d points... So how to select K most distant rows (points) from N (with any complexity)?