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https://issues.apache.org/jira/browse/SPARK-22586?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jorge Gonzalez Lopez updated SPARK-22586:
-----------------------------------------
    Description: 
Hello everyone, 

I would like to know if there are plans to add different score functions to 
perform feature selection under the same interface. I saw two previous issues 
related to the topic:

https://issues.apache.org/jira/browse/SPARK-6531
https://issues.apache.org/jira/browse/SPARK-1473

However, it seems nothing was added at the end. I would like to know if there 
was some problem then, because I wouldn't mind taking a closer look to it in 
case people would be interested. 

Additionally, I think it would be interested to include a score metric between 
continuous attributes (for regression), and between continuous and discrete 
(for classification). This has already been done successfully on 
http://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection

> Feature selection 
> ------------------
>
>                 Key: SPARK-22586
>                 URL: https://issues.apache.org/jira/browse/SPARK-22586
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.2.0
>            Reporter: Jorge Gonzalez Lopez
>            Priority: Minor
>
> Hello everyone, 
> I would like to know if there are plans to add different score functions to 
> perform feature selection under the same interface. I saw two previous issues 
> related to the topic:
> https://issues.apache.org/jira/browse/SPARK-6531
> https://issues.apache.org/jira/browse/SPARK-1473
> However, it seems nothing was added at the end. I would like to know if there 
> was some problem then, because I wouldn't mind taking a closer look to it in 
> case people would be interested. 
> Additionally, I think it would be interested to include a score metric 
> between continuous attributes (for regression), and between continuous and 
> discrete (for classification). This has already been done successfully on 
> http://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection



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