GitHub user mpjlu opened a pull request:
https://github.com/apache/spark/pull/14597
Fpr chi square
## What changes were proposed in this pull request?
Univariate feature selection works by selecting the best features based on
univariate statistical tests. False Positive Rate (FPR) is a popular univariate
statistical test for feature selection. We add a chiSquare Selector based on
False Positive Rate (FPR) test in this PR, like it is implemented in
scikit-learn.
http://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection
## How was this patch tested?
Add Scala ut
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mpjlu/spark fprChiSquare
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14597.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 #14597
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commit 2adebe8de3881509e510fc518c562d1141ccd0ef
Author: Peng, Meng <peng.m...@intel.com>
Date: 2016-08-10T05:40:18Z
add a chiSquare Selector based on False Positive Rate (FPR) test
commit 04053ca207ef4aa955eddc3e65d09a4e03db6292
Author: Peng, Meng <peng.m...@intel.com>
Date: 2016-08-11T07:10:43Z
Merge remote-tracking branch 'origin/master' into fprChiSquare
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