On Saturday 29 March 2008, Ted Dunning wrote: > SVM is not the only solution to these problems. For many search engine > applications, it isn't even likely to be the best. Regularized logistic > regression is a strong candidate as are random forests and boosted trees.
There have been several interesting papers on ranking search results based on preferences on NIPS 2007. The algorithms presented therein optimise exactly the criterion used to evaluate search engine rankings. In some cases they also compare against the svm solution of Thorsten Joachims. > The algorithm may well have some > virtues, but it is unlikely to be universal. There is even an "official theorem" for your statement: the no-free-lunch theorem :) > It is more likely that the author who claims this simply has a limited view > of the range of things that might need to be done. Or that he just examined the algorithm from exactly one angle that might not be the one that is important for your problem. Isabel -- Flattery is like cologne -- to be smelled, but not swallowed. -- Josh Billings |\ _,,,---,,_ Web: <http://www.isabel-drost.de> /,`.-'`' -. ;-;;,_ |,4- ) )-,_..;\ ( `'-' '---''(_/--' `-'\_) (fL) IM: <xmpp://[EMAIL PROTECTED]>
signature.asc
Description: This is a digitally signed message part.
