So I had a thought, tried it out, and liked what it did. I'm sure someone else has done this. It feels very convenient. It also gives an interesting take on robust nonparametric density estimation.
- copy the dataset so I'm not deleting all the data
- while the number of elements remaining in the data is above target percentage
- Find the convex hull of the data
- remove those points from the data
- calculate the number of remaining points
- At the target level of remaining points, determine and plot the convex hull
Can you tell me what the actual process is called, point to some papers, and possibly criticisms showing its weaknesses?