Hi Sebastian - sorry about the lack of activity here. I've looked at the scala dsl, but I think it makes more sense to push this work into MLLib as it really relies on spark streaming and RDDs. I'm not how you would build the streaming abstraction within the current DSL setup. Let me know if I'm missing something.
On 17 May 2014 23:23, Sebastian Schelter (JIRA) <j...@apache.org> wrote: > > [ > https://issues.apache.org/jira/browse/MAHOUT-1153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel > ] > > Sebastian Schelter resolved MAHOUT-1153. > ---------------------------------------- > > Resolution: Won't Fix > > no activity for more than a month > >> Implement streaming random forests >> ---------------------------------- >> >> Key: MAHOUT-1153 >> URL: https://issues.apache.org/jira/browse/MAHOUT-1153 >> Project: Mahout >> Issue Type: New Feature >> Components: Classification >> Reporter: Andy Twigg >> Labels: features >> Fix For: 1.0 >> >> >> The current random forest implementations are in-core and not scalable. This >> issue is to add an out-of-core, scalable, streaming implementation. >> Initially it could be based on [1], and using mappers in a master-worker >> style. >> [1] http://jmlr.csail.mit.edu/papers/volume11/ben-haim10a/ben-haim10a.pdf > > > > -- > This message was sent by Atlassian JIRA > (v6.2#6252)
