Cardinality should be set to whatever the logical dimension of the vector is -- it shouldn't be arbitrary. It's not like an "initial size" of a list. If your'e dealing with vectors that have a potentially unbounded maximum dimension, use Integer.MAX_VALUE.
As the name suggests, the implementation you use is for sparse vectors, meaning dimensions without value have no representation. It would be a pretty poor sparse implementation if these were not true. So, no, the cardinality has no direct effect on memory. On Fri, Jul 15, 2011 at 1:00 PM, marco turchi <marco.tur...@gmail.com> wrote: > Hi > thanks a lot > > I have also another problem ( :-) ). As I wrote in the previous email, I'm > using the RandomAccessSparseVector representation to store sparse vectors. I > need to sum some of them together, so I use the method plus but it seems > that it requires the same vector cardinality. I set the initial cardinality > of each vector to a big value, but I was wondering if it is a huge waste of > memory or everything is optimized inside the RandomAccessSparseVector > class. In case, is there an optimal way to set the cardinality? > > Thanks again > Marco > > On Fri, Jul 15, 2011 at 1:50 PM, Sean Owen <sro...@gmail.com> wrote: > >> This is simply Euclidean distance squared. Take the square root if you >> need the simple Euclidean distance. >> >> On Fri, Jul 15, 2011 at 12:36 PM, marco turchi <marco.tur...@gmail.com> >> wrote: >> > Dear All, >> > I'm a newcomer in Mahout and I'm try to compute the cosine similarity >> > between two sparse vectors. >> > I have loaded them using the class RandomAccessSparseVector. I notice >> that >> > there is a method called: getDistanceSquared. Which kind of vector >> distance >> > is implemented? Is there a method to compute directly this distance? >> > >> > Thanks a lot in advance for your help >> > Marco >> > >> >
