[jira] [Updated] (SPARK-16105) PCA Reverse Transformer

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-16105?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen updated SPARK-16105:
------------------------------
       Flags:   (was: Important)
    Priority: Minor  (was: Major)

The transformation is to a lower-dimensional space, so it's not possible in general to reverse it. You can, but you still end up with a 15-dimensional subspace of 96-dimensional space in your example. The matrix is all the information available to make this transformation and it's available already.

> PCA Reverse Transformer
> -----------------------
>
>                 Key: SPARK-16105
>                 URL: https://issues.apache.org/jira/browse/SPARK-16105
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>    Affects Versions: 1.6.1
>            Reporter: Stefan Panayotov
>            Priority: Minor
>
> The PCA class has a fit method that returns a PCAModel. One of the members of the PCAModel is a pc (Principal Components Matrix). This matrix is available for inspection, but there is no method to use this matrix for reverse transformation back to the original dimension. For example, if I use the PCA to reduce dimensionality of my space from 96 to 15, I get a 96x15 pc Matrix. I can do some modeling in my reduced space and then I need to  reverse back to the original 96 dimensional space. Basically, I need to multiply my 15 dimensional vectors by the 96x15 pc Matrix to get back 96 dimensional vectors. Such method is missing from the PCA model.



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