Hi Dmitri, We have a mahout mirror from github but I don't see any of the math-scala code.
Where do I see the math-scala code ? I thought github mirror is updated with svn repo. Thanks. Deb On Fri, Jan 3, 2014 at 10:43 AM, Dmitriy Lyubimov <[email protected]> wrote: > > > > On Fri, Jan 3, 2014 at 10:28 AM, Sebastian Schelter <[email protected]>wrote: > >> > I wonder if anyone might have recommendation on scala native >> implementation >> > of SVD. >> >> Mahout has a scala implementation of an SVD variant called Stochastic SVD: >> >> >> https://svn.apache.org/viewvc/mahout/trunk/math-scala/src/main/scala/org/apache/mahout/math/scalabindings/SSVD.scala?view=markup > > > Mahout also has SVD and Eigen decompositions mapped to scala as svd() and > eigen(). Unfortunately i have not put it on wiki yet but the summary is > available here https://issues.apache.org/jira/browse/MAHOUT-1297 > > Mahout also has distributed PCA implementation (which is based on > distributed Stochastic SVD and has a special provisions for sparse matrix > cases). Unfortunately our wiki is in flux now due to migration off > confluence to CMS so the SSVD page has not yet been migrated to CMS so > confluence version is here > https://cwiki.apache.org/confluence/display/MAHOUT/Stochastic+Singular+Value+Decomposition > > >> >> Otherwise, all the major java math libraries (mahout math, jblas, >> commons-math) should provide an implementation that you can use in scala. >> >> --sebastian >> >> > C >> > >> > >> > >> > >> > On Thu, Jan 2, 2014 at 7:06 PM, Ameet Talwalkar < >> [email protected]>wrote: >> > >> >> Hi Deb, >> >> >> >> Thanks for your email. We currently do not have a DSGD implementation >> in >> >> MLlib. Also, just to clarify, DSGD is not a variant of ALS, but rather >> a >> >> different algorithm for solving the same the same bi-convex objective >> >> function. >> >> >> >> It would be a good thing to do add, but to the best of my knowledge, no >> >> one is actively working on this right now. >> >> >> >> Also, as you mentioned, the ALS implementation in mllib is more >> >> robust/scalable than the one in spark.examples. >> >> >> >> -Ameet >> >> >> >> >> >> On Thu, Jan 2, 2014 at 3:16 PM, Debasish Das <[email protected] >> >wrote: >> >> >> >>> Hi, >> >>> >> >>> I am not noticing any DSGD implementation of ALS in Spark. >> >>> >> >>> There are two ALS implementations. >> >>> >> >>> org.apache.spark.examples.SparkALS does not run on large matrices and >> >>> seems more like a demo code. >> >>> >> >>> org.apache.spark.mllib.recommendation.ALS looks feels more robust >> version >> >>> and I am experimenting with it. >> >>> >> >>> References here are Jellyfish, Twitter's implementation of Jellyfish >> >>> called Scalafish, Google paper called Sparkler and similar idea put >> forward >> >>> by IBM paper by Gemulla et al. (large-scale matrix factorization with >> >>> distributed stochastic gradient descent) >> >>> >> >>> https://github.com/azymnis/scalafish >> >>> >> >>> Are there any plans of adding DSGD in Spark or there are any existing >> >>> JIRA ? >> >>> >> >>> Thanks. >> >>> Deb >> >>> >> >>> >> >> >> > >> > >> >> >
