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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/06/03 16:12:40 UTC
[jira] [Assigned] (SPARK-7334) Implement RandomProjection for
Dimensionality Reduction
[ https://issues.apache.org/jira/browse/SPARK-7334?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-7334:
-----------------------------------
Assignee: (was: Apache Spark)
> Implement RandomProjection for Dimensionality Reduction
> -------------------------------------------------------
>
> Key: SPARK-7334
> URL: https://issues.apache.org/jira/browse/SPARK-7334
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Sebastian Alfers
> Priority: Minor
>
> Implement RandomProjection (RP) for dimensionality reduction
> RP is a popular approach to reduce the amount of data while preserving a reasonable amount of information (pairwise distance) of you data [1][2]
> - [1] http://www.yaroslavvb.com/papers/achlioptas-database.pdf
> - [2] http://people.inf.elte.hu/fekete/algoritmusok_msc/dimenzio_csokkentes/randon_projection_kdd.pdf
> I compared different implementations of that algorithm:
> - https://github.com/sebastian-alfers/random-projection-python
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