There is a packed symmetric matrix impl in the Stochastic SVD stuff, but it is hard-coded to a packed implementation. org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular - mahout/math
You could recode this to use the Vector class for storage. Be sure to run all of the Matrix unit tests if you do this; Matrix has a lot of things that can go wrong. On Sat, Jan 14, 2012 at 2:03 AM, Tamas Jambor <[email protected]> wrote: > thanks, ideally I would need both symmetric and diagonal. > > On Sat, Jan 14, 2012 at 8:26 AM, Sebastian Schelter <[email protected]> wrote: > >> I think Tamas referred to matrices that are symmetric (only the upper >> triangular half would need to be stored) not diagonal matrices. >> >> >> On 14.01.2012 05:25, Lance Norskog wrote: >> > org.apache.mahout.math.DiagonalMatrix >> > >> > It even supports sparse values in the diagonal! >> > >> > On Fri, Jan 13, 2012 at 9:00 AM, Tamas Jambor (Commented) (JIRA) >> > <[email protected]> wrote: >> >> >> >> [ >> https://issues.apache.org/jira/browse/MAHOUT-737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13185670#comment-13185670] >> >> >> >> Tamas Jambor commented on MAHOUT-737: >> >> ------------------------------------- >> >> >> >> I think so. When will you be releasing 0.6? I am planning to do a bit >> more extensive testing in the next 2-3 weeks. >> >> >> >>> Implicit Alternating Least Squares SVD >> >>> -------------------------------------- >> >>> >> >>> Key: MAHOUT-737 >> >>> URL: https://issues.apache.org/jira/browse/MAHOUT-737 >> >>> Project: Mahout >> >>> Issue Type: New Feature >> >>> Components: Collaborative Filtering >> >>> Affects Versions: 0.6 >> >>> Reporter: Tamas Jambor >> >>> Assignee: Sebastian Schelter >> >>> Attachments: MAHOUT-737-2.patch, MAHOUT-737.patch, >> MAHOUT-737.patch, MAHOUT-737.patch, MAHOUT-737.patch >> >>> >> >>> >> >>> I am sharing this Java implementation of mine that is based on the >> paper - Collaborative Filtering with Implicit Datasets. The implementation >> is multi-treading and can be easily extended to use it on Hadoop. In fact >> this approach would possibly work with non-implicit datasets, but further >> testing is needed. The algorithm is tried and tested on an implicit >> TV-viewing dataset, and the performance was pretty good (details to follow). >> >> >> >> -- >> >> This message is automatically generated by JIRA. >> >> If you think it was sent incorrectly, please contact your JIRA >> administrators: >> https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa >> >> For more information on JIRA, see: >> http://www.atlassian.com/software/jira >> >> >> >> >> > >> > >> > >> >> -- Lance Norskog [email protected]
