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author | Peng, Meng <peng.meng@intel.com> | 2016-09-21 10:17:38 +0100 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-09-21 10:17:38 +0100 |
commit | b366f18496e1ce8bd20fe58a0245ef7d91819a03 (patch) | |
tree | 3a2e189a94ad1fc49040d721eb586724bc493097 /bin/load-spark-env.cmd | |
parent | 28fafa3ee8f3478fa441e7bd6c8fd4ab482ca98e (diff) | |
download | spark-b366f18496e1ce8bd20fe58a0245ef7d91819a03.tar.gz spark-b366f18496e1ce8bd20fe58a0245ef7d91819a03.tar.bz2 spark-b366f18496e1ce8bd20fe58a0245ef7d91819a03.zip |
[SPARK-17017][MLLIB][ML] add a chiSquare Selector based on False Positive Rate (FPR) test
## 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
Author: Peng, Meng <peng.meng@intel.com>
Closes #14597 from mpjlu/fprChiSquare.
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