zhengruifeng created SPARK-14022:
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Summary: 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: Question
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.
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