On 22 May 2018 at 15:02, Paul A. Bristow via Boost
-----Original Message----- From: Boost [mailto:boost-bounces@lists.boost.org] On Behalf Of Raffi Enficiaud via Boost Sent: 11 May 2018 20:24 To: boost@lists.boost.org Cc: Raffi Enficiaud Subject: [boost] Interest in a tiny kmeans library
Dear all,
We are finishing the cleanup of a tiny kmeans library. For those who do not know, kmeans is a widely used data clustering algorithm.
This special implementation has a lower runtime complexity by taking advantages of the triangle inequalities between clusters and data points at each iteration. This implementation is based on the paper of Charles Elkan https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
We have also python and matlab bindings, fully generic on the data type, and with additional initialization heuristics.
I would be happy if we can release this library into Boost. Do you think there is any interest for the community?
This is niche stuff, but I suspect useful nonetheless.
Do not be discouraged by immediate lack of interest.
But you may need to find some users to press your case.
(And don't forget the need for good Boost-style docs).
I second that. I could potentially use it myself, so I'd be interested in seeing it proposed. (with good docs, of course :)) Best regards, -- Mateusz Loskot, http://mateusz.loskot.net