Hello all, I've been investigating clustering algorithms with special interest in non-parametric methods and, one that is being mentioned quite often is DBCLASD [1]. I've looked around but I haven't been able to find one single implementation of this algorithm whatsoever so I decided to implement my own.
My first running version is already on GitHub: https://goo.gl/V4HOVH I tried to make it as simple as possible for anyone to run it: it's all written in Python, requires only "standard" python packages (numpy, scikit-learn, scipy and matplotlib) and it comes with a main routine that runs an example. I would really appreciate some feedback from the community, regarding the correctness of this implementation (if you happen to have some experience with the algorithm) and perhaps a discussion about how useful this algorithm may be in order to decide whether it makes sense to integrate it into a future version of scikit-learn or not. Thanks in advance for your time :-) Regards, Sebastian
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