[
https://issues.apache.org/jira/browse/MAHOUT-771?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13086800#comment-13086800
]
Lance Norskog commented on MAHOUT-771:
--------------------------------------
It's one of these simple ideas where the actual code comes out differently for
each implementation. As mentioned, I'm using it for visualization. It has to
compete with SVD for the quality of the output vectors, so a better generator
seemed appropriate.
Is there a place for visualization in Mahout-land? The structure of viz
software is somewhat different than Java libraries. It's all about mashups and
random useful libraries. Builds are hard to script. The sample programs for
displaying clusters are written in AWT, one of the skankiest libraries around
just because it is in the JDK.
Is there a use for this concept in projecting matrices?
> Random Projection using sampled values
> --------------------------------------
>
> Key: MAHOUT-771
> URL: https://issues.apache.org/jira/browse/MAHOUT-771
> Project: Mahout
> Issue Type: New Feature
> Components: Math
> Reporter: Lance Norskog
> Priority: Minor
> Attachments: RandomProjector.patch, RandomProjectorBenchmark.java
>
>
> Random Projection implementation which follows two deterministic guarantees:
> # The same data projected multiple times produces the same output
> # Dense and sparse data with the same contents produce the same output
> Custom class that does Random Projection based on Johnson-Lindenstrauss. This
> implementation uses Achlioptas's results, which allow using method other than
> a full-range random multiplier per sample:
> * use 1 random bit to add or subtract a sample to a row sum
> * use a random value from 1/6 to add (1/6), subtract (1/6), or ignore (4 out
> of 6) a sample to a row sum
> Custom implementations for both dense and sparse vectors are included. The
> sparse vector implementation assumes the active values will fit in memory.
> An implementation using full-range random multipliers made by
> java.util.Random is included for reference/research.
> *Database-friendly random projections: Johnson-Lindenstrauss with binary
> coins*
> _Dimitris Achlioptas_
> [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.84.4546&rep=rep1&type=pdf]
--
This message is automatically generated by JIRA.
For more information on JIRA, see: http://www.atlassian.com/software/jira
