Perhaps this page <http://mahout.apache.org/users/basics/algorithms.html> needs to be updated with algorithms and features of 0.11.0?
On 19 October 2015 at 18:29, Pat Ferrel <[email protected]> wrote: > BTW this use of Mahout-Samsara on Spark for recs has really expanded. The > Samsara part I’m calling a Correlation Engine, it can be used to mix usage, > content, and context to make recs. I look back on 2 years ago as pretty > much groping around for solutions. Things are much clearer now (for me at > least) > > Check out some slides about the math, leading to the “whole enchilada” > equation. Ted Dunning, Sean Owen, and Sebastian Schelter get no small > credit. > http://www.slideshare.net/pferrel/unified-recommender-39986309 > > Even have code running using the PredicitonIO framework. This includesa > SDK to event store to realtime query. Loosely speaking a lambda > architecture. Most of the whole enchilada running except the content part > of the equation, which only works on metadata for how. > https://github.com/pferrel/scala-parallel-universal-recommendation > > We even do custom versions at actionML.com > > > On Oct 19, 2015, at 6:42 AM, Sean Owen <[email protected]> wrote: > > No, this is pretty wrong. Spark is not, in general, a real-time > anything. Spark Streaming is a near-real-time streaming framework, but > it is not something you can build models with. Spark MLlib / ML are > offline / batch. Not sure what you mean by Hadoop engine, but Spark > does not build on MapReduce, if that's what you mean. > > The "classic" Mahout code (<= 0.9) is definitely deprecated. The "new" > Mahout is not. It has a fairly different new recommender system called > Samsara. It has Scala APIs. In fact, it uses Spark. I think you're > somehow talking about the "classic" Mahout code here only. > > On Mon, Oct 19, 2015 at 2:38 PM, Fei Shan <[email protected]> > wrote: > > Spark is a in memory , near realtime Machine Learning frameowork , has > > scala and java interface > > Mahout is an offline Machine Learning framework, no scala apis > > > > they both built on the HDFS and Hadoop engine > > > > Spark has an ecosystem like Hadoop > > Mahout is part of of Hadoop ecosystem > > > > Spark could beat Mahout on processing speed > > and concise programming APIs > > > > for online data anaysis , Spark is a better choice. > > for offline data analysis, both fits well. > > > > > > > > On Mon, Oct 19, 2015 at 9:14 PM, Prasad Priyadarshana Fernando < > > [email protected]> wrote: > > > >> Hi, > >> > >> If I have used Mahout for my recommendation application, should I > migrate > >> into Spark MLib technology? Is the mahout still supported and migrated? > >> > >> Thanks > >> > >> *Prasad Priyadarshana Fernando < > http://www.linkedin.com/in/prasadfernando > >>> * > >> Mobile: +1 330 283 5827 > >> > >
