>> I'm not sure if "flat geometry" is a good way to describe the case that >> KMeans works in. I would have said "convex clusters". Not sure in how far >> that applies to hierarchical clustering, though. >> > Euclidean distance. > Can you please elaborate? >> Also, I would mention explicitly that often clustering algorithms are >> evaluated using ARI or AMI using classification data, since there >> is not really any other data available, and why this is bad ;) >> > Can you contribute a sentence for this, I don't feel confortable enough. > > Ok, I have to think about it, though ;)
>> I am just working on a clustering algorithm and it is really hard to >> say what it means for a clustering algorithm to fail. >> > Yes, indeed :$ > > Just know I have 4 plots of clustering algorithms on my desktop, one of which I want to publish. Problem is: the clustering does not agree with the classes, while the kmeans results do. Now what? -_- >> Oh and one more thing: For spectral clustering, I think we implement >> the Shi/Malik version, not the Jordan/Ng version. Though adding >> this as an option would probably be quite easy. This should probably >> also be made explicit in the docs. >> > I never heard of the latter (excuse my ignorance). But I am curious. > > I just wrote down an explanation of quickshift (since I wrote something about that and it is little know) and while pressing on 'send' I read that you didn't know about Jordan/Ng ^^ They published basically at the same time as Shi/Malik and the work is closely related. In the tutorial that is linked in the docs there is a nice explanation. Basically Shi/Malik multipy by the inverse diagonal from the right while Jordan/Ng multiply by the square root form left and right - or something ;) > > $ git fetch gael > $ git diff gael/master > > Had I done a separate branch, it would have been easier. Sorry. > > Np. Thanks for the command :) ------------------------------------------------------------------------------ This SF email is sponsosred by: Try Windows Azure free for 90 days Click Here http://p.sf.net/sfu/sfd2d-msazure _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
