Hi Dmitry, I've pulled this out as a separate issue under MAHOUT-923. Could you please take a look?
Thanks! On Dec 8, 2011, at 11:38 AM, "Dmitriy Lyubimov (Issue Comment Edited) (JIRA)" <j...@apache.org> wrote: > > [ > https://issues.apache.org/jira/browse/MAHOUT-880?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13165469#comment-13165469 > ] > > Dmitriy Lyubimov edited comment on MAHOUT-880 at 12/8/11 7:36 PM: > ------------------------------------------------------------------ > > Ideally to optimize this i guess DRM better have a notion that dimensions (or > whatever other parameters inside solver) may not be initially known. When > this happens, first operation in pipeline (whatever it happens to be) may > also employ standard strategies to come up with those in the end. > > Similarly, there's a "post-step" strategy concept: using output and some > additional parameters you can re-assemble required knowledge (such as mean or > small result of multiplication) in post step by re-combining result of all > reducers or separate factors of computation (if it happens to be a small > product in the end). > > this is a fundamental technique in SSVD (and seems to become even more > prominent with PCA efficiency tricks). > > was (Author: dlyubimov): > Ideally to optimize this i guess DRM better have a notion that dimensions > (or whatever other parameters inside solver) may not be initially known. When > this happens, first operation in pipeline (whatever it happens to be) may > also employ standard strategies to come up with those in the end. > > Similarly, there's a "post-step" strategy concept: using output and some > additional parameters you can re-assemble required knowledge (such as mean or > small result of multiplication) in post step by re-combining result of all > reducers or separate factors of computation (if it happens to be a small > product in the end). > > this is a fundamental technique and SSVD (and seems to become even more > prominent with PCA efficiency tricks). > >> Add some matrix method(like addition, subtraction, norm ... etc) to >> DistributedRowMatrix >> ---------------------------------------------------------------------------------------- >> >> Key: MAHOUT-880 >> URL: https://issues.apache.org/jira/browse/MAHOUT-880 >> Project: Mahout >> Issue Type: New Feature >> Components: Math >> Affects Versions: 0.6 >> Reporter: Wangda Tan >> Priority: Minor >> Labels: DistributedRowMatrix >> Attachments: MAHOUT-880.patch, MAHOUT-880.patch, MAHOUT-880.patch >> >> >> I'm a new to Mahout, I didn't find some basic matrix functions. This make >> users cannot do many tasks by CLI or API, if user get some result through >> existing map-reduce matrix operation (like svd), he cannot do farther steps. >> I make a list for it: >> 1) Addition, Subtraction >> 2) Norm (like norm-1, norm-2, norm-frobenius) >> 3) Matrix compare >> 4) Get lower triangle, upper triangle and diagonal >> 5) Get identity and zero matrix >> 6) Put two or matrix to together: A = [A1, A2] >> 7) More linear equations solver method, like Gaussian elimination (maybe >> it's hard to implement) >> 8) import and export CSV, ARFF ... (this will very useful when user want to >> reuse result from or to other applications like MATLAB) >> I want to know is there any plan to do this, if so, I can make some efforts >> to implement these. > > -- > 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 > >
