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https://issues.apache.org/jira/browse/SPARK-17870?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15565180#comment-15565180
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Sean Owen commented on SPARK-17870:
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I don't think the raw statistic can be directly compared here because the
features do not have even nearly the same number of 'buckets', not necessarily.
A given test statistic value is "less remarkable" when there are more DoF;
what's high for a binary-valued feature may not be high at all for one taking
on 100 values.
Does scikit really use the statistic? because you're also saying it does
something that gives different results from ranking on the statistic.
> ML/MLLIB: Statistics.chiSqTest(RDD) is wrong
> ---------------------------------------------
>
> Key: SPARK-17870
> URL: https://issues.apache.org/jira/browse/SPARK-17870
> Project: Spark
> Issue Type: Bug
> Components: ML, MLlib
> Reporter: Peng Meng
> Priority: Critical
>
> The method to count ChiSqureTestResult in mllib/feature/ChiSqSelector.scala
> (line 233) is wrong.
> For feature selection method ChiSquareSelector, it is based on the
> ChiSquareTestResult.statistic (ChiSqure value) to select the features. It
> select the features with the largest ChiSqure value. But the Degree of
> Freedom (df) of ChiSqure value is different in Statistics.chiSqTest(RDD), and
> for different df, you cannot base on ChiSqure value to select features.
> Because of the wrong method to count ChiSquare value, the feature selection
> results are strange.
> Take the test suite in ml/feature/ChiSqSelectorSuite.scala as an example:
> If use selectKBest to select: the feature 3 will be selected.
> If use selectFpr to select: feature 1 and 2 will be selected.
> This is strange.
> I use scikit learn to test the same data with the same parameters.
> When use selectKBest to select: feature 1 will be selected.
> When use selectFpr to select: feature 1 and 2 will be selected.
> This result is make sense. because the df of each feature in scikit learn is
> the same.
> I plan to submit a PR for this problem.
>
>
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