GitHub user dbtsai opened a pull request:
https://github.com/apache/spark/pull/1207
SPARK-2272 [MLlib] Feature scaling which standardizes the range of
independent variables or features of data
Feature scaling is a method used to standardize the range of independent
variables or features of data. In data processing, it is also known as data
normalization and is generally performed during the data preprocessing step.
In this work, a trait called `VectorTransformer` is defined for generic
transformation of a vector. It contains two methods, `apply` which applies
transformation on a vector and `unapply` which applies inverse transformation
on a vector.
There are three concrete implementations of `VectorTransformer`, and they
all can be easily extended with PMML transformation support.
1) `VectorStandardizer` - Standardises a vector given the mean and
variance. Since the standardization will densify the output, the output is
always in dense vector format.
2) `VectorRescaler` - Rescales a vector into target range specified by a
tuple of two double values or two vectors as new target minimum and maximum.
Since the rescaling will substrate the minimum of each column first, the output
will always be in dense vector regardless of input vector type.
3) `VectorDivider` - Transforms a vector by dividing a constant or diving a
vector with element by element basis. This transformation will preserve the
type of input vector without densifying the result.
Utility helper methods are implemented for taking an input of RDD[Vector],
and then transformed RDD[Vector] and transformer are returned for dividing,
rescaling, normalization, and standardization.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/dbtsai/spark dbtsai-feature-scaling
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/1207.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1207
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commit d3daa997c9a51a4af8f67cbcdb3738e5ba8c4b56
Author: DB Tsai <dbt...@alpinenow.com>
Date: 2014-06-25T02:30:16Z
Feature scaling which standardizes the range of independent variables or
features of data.
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