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From "Joseph K. Bradley (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-18088) ChiSqSelector FPR PR cleanups
Date Tue, 25 Oct 2016 06:01:58 GMT

     [ https://issues.apache.org/jira/browse/SPARK-18088?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Joseph K. Bradley updated SPARK-18088:
--------------------------------------
    Description: 
There are several cleanups I'd like to make as a follow-up to the PRs from [SPARK-17017]:
* Clarify FPR, alpha, p-value relationship in docs and param naming
** I'd like to remove "alpha" since it is such a generic name.
* Rename selectorType values to match corresponding Params
* Add Since tags where missing
* a few minor cleanups

One major item: FPR is not implemented correctly.  Testing against only the p-value and not
the test statistic does not really tell you anything.  We should follow sklearn's default
for starters: [http://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html#sklearn.feature_selection.f_classif]

  was:
There are several cleanups I'd like to make as a follow-up to the PRs from [SPARK-17017]:
* Clarify FPR, alpha, p-value relationship in docs and param naming
** I'd like to remove "alpha" since it is such a generic name.
* Rename selectorType values to match corresponding Params
* Add Since tags where missing
* a few minor cleanups


> ChiSqSelector FPR PR cleanups
> -----------------------------
>
>                 Key: SPARK-18088
>                 URL: https://issues.apache.org/jira/browse/SPARK-18088
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: Joseph K. Bradley
>            Assignee: Joseph K. Bradley
>            Priority: Minor
>
> There are several cleanups I'd like to make as a follow-up to the PRs from [SPARK-17017]:
> * Clarify FPR, alpha, p-value relationship in docs and param naming
> ** I'd like to remove "alpha" since it is such a generic name.
> * Rename selectorType values to match corresponding Params
> * Add Since tags where missing
> * a few minor cleanups
> One major item: FPR is not implemented correctly.  Testing against only the p-value and
not the test statistic does not really tell you anything.  We should follow sklearn's default
for starters: [http://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html#sklearn.feature_selection.f_classif]



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