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I agree that on some level more data sets would be nice, but I felt that it cluttered and obscured the exposition. Instead I used the one synthetic dataset, but
by lmcinnes 10y ago
I agree that on some level more data sets would be nice, but I felt that it cluttered and obscured the exposition. Instead I used the one synthetic dataset, but crafted in to have various properties (noise, cluster shape, variable density, non-standard distributions) that will confound many different clustering approaches ... it is meant to be the "hard" case that with all the difficulties and confounding factors rolled into one dataset.
- mattnedrich 10y agoCool, I think you did a great job. Do you have run time data for each algorithm on that data set?
- lmcinnes 10y agoIt's included in the upper left corner of the plots. To be fair, these are for the sklearn implementations, some of which are excellent, but I can't speak for the performance of all of them.