[scikit-learn] Adding Quickshift clustering algorithm
heinrich.jiang at gmail.com
Mon Oct 8 00:02:37 EDT 2018
I'm a researcher at Google Research and I am writing to initiate discussion
about adding Quickshift as well as a variant of it as part of
scikit-learn's set of clustering algorithms.
This somewhat recent algorithm was designed as a faster alternative to Mean
Shift and has been used extensively in computer vision (and already part of
scikit-image). The method was published independently in these papers
[1,2].  has 600 citations and  has 1300 citations.
 Vedaldi, Andrea, and Stefano Soatto. "Quick shift and kernel methods
for mode seeking." *European Conference on Computer Vision*. Springer,
Berlin, Heidelberg, 2008.
 Rodriguez, Alex, and Alessandro Laio. "Clustering by fast search and
find of density peaks." *Science* 344.6191 (2014): 1492-1496.
In addition to Quickshift, I also propose a variant called Quickshift++,
which is Quickshift with an additional hyperparameter. We showed in 
that this substantially improved performance over Quickshift as well as
other clustering algorithms implemented in sklearn on benchmark datasets.
(i.e. Figure 9 in https://arxiv.org/abs/1805.07909) and was published at
 Jiang, Heinrich, Jennifer Jang, and Samory Kpotufe. "Quickshift++:
Provably Good Initializations for Sample-Based Mean Shift." ICML 2018
We have an implementation here (https://github.com/google/quickshift).
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