http://computationalmedicine.org/home-0
Very noisy and sparse data. 25 teams. 22 system description papers. The winner used SVM ensamble.
I work in computer vision. When I do a machine learning problem, I spend most of my time brainstorming and implementing good features. I'm getting deeper into ML (and loving it). I'm always curious what other people are doing with ML.
Yes, it would be great to get a list of hackers that do ML and the domain that they are working with.
I thought it was a good idea until I actually visited a casino. People sit at the slots in what looks like a hypnotic state. The emotions don't change much. I don't think I could have made a measurable difference.
I'm not surprised the gambling industry is using ml, but cool to hear about it. Thanks.
I tried to find a paper comparing an ensemble of SVM to an ensemble of trees and I came up empty (after a quick search). I did find papers showing ensembles of SVMs outperforming a single SVM. I also found a comment on a paper claiming an ensemble of trees out outperformed a "Parallel Mixture of SVM" (see here: http://www.mitpressjournals.org/doi/abs/10.1162/089976604323...). Of course, that's not a great source.
I absolutely agree they should have included ensembles other than trees. I don't necessarily agree an ensemble of SVM would have beat an ensemble of trees. It would have been interesting to see.