I would have folded them all as different feature ids in a single vector, makes things a lot simpler and faster.
Robin Anil | Software Engineer | +1 312 869 2602 | Google Inc. On Thu, Apr 11, 2013 at 11:19 AM, Gokhan Capan <gkhn...@gmail.com> wrote: > Hi Robin, > > If you are asking why they are arrays, it is because to save clients from > concatenating multiple matrices to create the input. > > I am quoting from libFM > paper<http://www.csie.ntu.edu.tw/~b97053/paper/Factorization%20Machines%20with%20libFM.pdf>: > "For easier interpretation, > the features are grouped into indicators for the active user (blue), > active item (red), other movies rated > by the same user (orange), the time in months (green), and the last movie > rated (brown)." > > I thought a client would create multiple group of matrices, and he can > just pass them all to the algorithm. > > Then the wModel is w parameters, it is still array of vectors for me to > keep the indexing consistent, and vModel is the V parameters. > > Was that what you were asking? > > > On Thu, Apr 11, 2013 at 6:44 PM, Robin Anil <robin.a...@gmail.com> wrote: > >> Comments away. I was a bit confused by the use of Vector[] for w1 and >> Matrix[] for inputs. >> >> Robin Anil | Software Engineer | +1 312 869 2602 | Google Inc. >> >> >> On Thu, Apr 11, 2013 at 10:00 AM, Gokhan Capan <gkhn...@gmail.com> wrote: >> >>> Ted, >>> Robin, >>> >>> Although I did not test on a dataset yet, recently I've been >>> implementing Factorization Machines with SGD optimization. >>> >>> The initial implementation is at >>> https://github.com/gcapan/mahout/tree/fm >>> >>> Would you guys consider to take a look so I can make it better and >>> running? >>> >>> >>> >>> On Mon, Apr 1, 2013 at 8:45 PM, Nkechi Nnadi <nkechi.nn...@gmail.com>wrote: >>> >>>> Hello, >>>> >>>> I'm long time lurker. I would be interested in implementing these. I >>>> thought I would get my feet wet with contributing to wiki with tutorials >>>> since I have used Mahout for recommendation and clustering in my >>>> dissertation. I have never contributed code before and I would love to >>>> start now. >>>> >>>> -Nkechi >>>> >>>> >>>> On Sun, Mar 31, 2013 at 1:14 PM, Robin Anil <robin.a...@gmail.com> >>>> wrote: >>>> >>>> > FMs work really well for a whole range of things. Having implemented >>>> them >>>> > myself, I can extend my services as a reviewer if anyone is willing to >>>> > start on it. >>>> > >>>> > Robin Anil | Software Engineer | +1 312 869 2602 | Google Inc. >>>> > >>>> > >>>> > On Sun, Mar 31, 2013 at 2:18 AM, Ted Dunning <ted.dunn...@gmail.com> >>>> > wrote: >>>> > >>>> > > Relative to Dan's recent mention of SOM as possible new project, >>>> here are >>>> > > slides from KDD Cup 2012 in which Stephen Rendle describes how he >>>> did >>>> > using >>>> > > a very straightforward implementation of Factorization Machines >>>> [1,2]. >>>> > > >>>> > > >>>> > > FMs are interesting in the context of Mahout because they can be >>>> used in >>>> > a >>>> > > wide variety of settings including recommendation and targeting and >>>> > because >>>> > > they have very good performance on a number of tasks. >>>> > > >>>> > > I should mention that Robin was the one who first mentioned FMs to >>>> me. >>>> > > >>>> > > The KDD 2012 competition [3] is of interest in any case because it >>>> > provides >>>> > > a large amount of realistic data for commercially important >>>> problems. >>>> > > >>>> > > [1] >>>> > > >>>> > > >>>> > >>>> https://kaggle2.blob.core.windows.net/competitions/kddcup2012/2748/media/RendleSlides.pdf >>>> > > >>>> > > [2] >>>> > > >>>> > > >>>> > >>>> https://kaggle2.blob.core.windows.net/competitions/kddcup2012/2748/media/Rendle.pdf >>>> > > >>>> > > [3] http://www.kddcup2012.org/ >>>> > > >>>> > >>>> >>> >>> >>> >>> -- >>> Gokhan >>> >> >> > > > -- > Gokhan >
