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Joseph K. Bradley commented on SPARK-7334: ------------------------------------------ I'd still like to get random projections and maybe other types of LSH into Spark, but it's true that having a package takes some of the pressure off of this goal. We're trying to figure out the roadmap for the next release currently, and that should give me a better idea of what can be prioritized. Thanks for your patience! > 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 -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org