One easy thing to do is to build an adjoined matrix type that does the concatenation on the fly.
On Thu, Apr 11, 2013 at 1:43 PM, Gokhan Capan <gkhn...@gmail.com> wrote: > Yeah, it is simpler indeed. > > I am going to think about alternative ways to make concatenation easier > for clients. > > Thanks for your review > > > On Thu, Apr 11, 2013 at 10:45 PM, Robin Anil <robin.a...@gmail.com> wrote: > >> 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 >>> >> >> > > > -- > Gokhan >
