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Parallel Enclosing Circle Algorithm (view source)
Revision as of 18:49, 17 November 2017
, 18:49, 17 November 2017→St. Louis bug
This image shows a rendering of the results of running St. Louis. There are four circles (the centers of circles are green dots), but two have radii of 0.0.
=== Progress on the bug ===
# Removing duplicate points from the data actually removes all of the errors, but this doesn't give you the solution with the smallest area.
# I tried removing duplicates but keeping track of a "count," though this reintroduces errors.
## % error before change (n=997 sample, A-Carlsbad):
## % error after change (n=997 sample):
# I narrowed down the bug to the constrained_kmeans method in ckmeans.py [https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/tr-2000-65.pdf (paper here)]
## For some reason, this returns clusters with smaller numbers of points than n
## [http://adared.ch/constrained-k-means-implementation-in-python/ This is a good overview of the algorithm]
# I wrote a plotter, the plot method in circles.py
== Related Pages ==
