I am not at home where I have my courses note about it, but you can have a look here for example: http://msrvideo.vo.msecnd.net/rmcvideos/144113/dl/144113.pdf page 50 you have a comparison between SVM and ELM, and ELM outperform SVM for the testing and training times.
It is not easy to give theoretical reasons why ELM are so quick compared to SVM, but they are. If someone seems to be interested to work on it with me, just tell me. 2013/4/30 Sean Owen <[email protected]> > If you care to work on it, you should work on it. Implementations > exist or don't exist because someone created it, or nobody was > interested in creating it. > > I have never heard of 'extreme learning' and found this summary: > > http://www.slideshare.net/formatc666/extreme-learning-machinetheory-and-applications > > If it's accurate, this is just describing a single hidden layer model > trained with back propagation. I don't see what's new? the part about > learning the beta weights is simple linear algebra. > > If it's just a hidden layer model, it's not necessarily better than SVMs, > no. > > On Tue, Apr 30, 2013 at 11:05 AM, Louis Hénault <[email protected]> > wrote: > > Hi everybody, > > > > Many people are trying to integrate SVM to Mahout. I can understand since > > SVM are really efficient in a "small data" context. > > But, as you may know, SVM has: > > -a slow learning speed > > -a poor learning scalability > > > > In contrast, ELM give results which are usually at least as good as SVM's > > and are something like 1000x faster. > > So, why not trying to work on this topic? > > > > (Sorry if someone already talked about it, I'm new on this mailing and > did > > not find anything after some researches) > > > > Regards >
