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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/11/01 21:12:59 UTC
[jira] [Commented] (SPARK-17459) Add Linear Discriminant to
dimensionality reduction algorithms
[ https://issues.apache.org/jira/browse/SPARK-17459?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15626687#comment-15626687 ]
Joseph K. Bradley commented on SPARK-17459:
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This sounds worth doing, but it will be important to get a committer to agree to help shepherd it. I'll try to revisit if I can, but hopefully others can pick it up before then.
Also, please don't set the Target Version or Shepherd fields; only committers should. Thanks!
> Add Linear Discriminant to dimensionality reduction algorithms
> --------------------------------------------------------------
>
> Key: SPARK-17459
> URL: https://issues.apache.org/jira/browse/SPARK-17459
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Joshua Howard
> Priority: Minor
>
> The goal is to add linear discriminant analysis as a method of dimensionality reduction. The algorithm and code are very similar to PCA, but instead project the data set onto vectors that provide class separation. LDA is a more effective alternative to PCA in terms of preprocessing for classification algorithms.
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