Sorry my mistake! LogLikelihoodSimilarity is giving me [0,1], however when I call GenericBooleanPrefUserBasedRecommender for the recommendation it is not giving me values [0,1]. That's what I meant.
* Agata Filiana Erasmus Mundus DMKM Student 2011-2013 <http://www.em-dmkm.eu/> * On 16 April 2013 15:58, Sean Owen <sro...@gmail.com> wrote: > That shouldn't be possible, are you sure? it's 1 - 1/(1+LLR) where LLR > is nonnegative. > Similarities are in [-1,1] and some are in [0,1]. > > On Tue, Apr 16, 2013 at 2:51 PM, Agata Filiana <a.filian...@gmail.com> > wrote: > > Hi Sean, > > > > I see your point. > > I think I better experiment with those different options. > > > > I'd also like to ask if the result of LogLikelihoodSimilarity is between > > [0,1] ? It seems that I'm getting results higher than 1. So if like you > > said combining the different attributes can be done by multiplying them > and > > normalizing them to [0,1] - what is the best method for normalization? > > >
