Offering non-classical hierarchical clustering techniques within scope?

[tlnagy]

Is it within the scope of this package to provide some more modern HC techniques (e.g. ROCK/CURE, BIRCH, etc)? Classical HC techniques (single-linkage, centroid linkage, etc) lack robustness and are sensitive to noise/outliers, plus their quadratic computational complexities are problematic when applying them to large datasets.

More modern algorithms like CURE can better handle multidimensional data and sophiscated cluster shapes. It has 2000+ citations on Google Scholar so there is definitely a large demand for HC techniques that can handle "big data". Wikipedia has the algorithm's pseudocode (I haven't checked it's validity).

[lindahua]

Yes, those are definitely in the scope of this package.

Contributions are appreciated!

[tlnagy]

I will likely have time in a week. I'll see what I come up with, it would be useful for my own research. Plus, anything that makes Julia more attractive helps my argument that my colleagues should switch away from MATLAB and Python.

[ararslan]

Hey @tlnagy, I realize it's been about 2 years since the last activity here. Are you still interested in contributing these clustering methods?

[tlnagy]

Unfortunately, my research interests have changed and I don't think I'll have the time to implementing these. I'm going to leave this issue open if any anyone is interested in methods and contributing them, but feel free to close if you deem this to be too niche.

[ararslan]

I think it'd be great to have them in here should anyone want to take it on. Thanks for the update and good luck with your research!