[ https://issues.apache.org/jira/browse/SPARK-14022?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
zhengruifeng updated SPARK-14022: --------------------------------- Issue Type: Brainstorming (was: Question) > What about adding RandomProjection to ML/MLLIB as a new dimensionality > reduction algorithm? > ------------------------------------------------------------------------------------------- > > Key: SPARK-14022 > URL: https://issues.apache.org/jira/browse/SPARK-14022 > Project: Spark > Issue Type: Brainstorming > Reporter: zhengruifeng > Priority: Minor > > What about adding RandomProjection to ML/MLLIB as a new dimensionality > reduction algorithm? > RandomProjection (https://en.wikipedia.org/wiki/Random_projection) reduces > the dimensionality by projecting the original input space on a randomly > generated matrix. > It is fully scalable, and runs fast (maybe fastest). > It was implemented in sklearn > (http://scikit-learn.org/stable/modules/random_projection.html) > I am be willing to do this, if needed. -- 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