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https://issues.apache.org/jira/browse/MADLIB-948?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15168231#comment-15168231
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ASF GitHub Bot commented on MADLIB-948:
---------------------------------------
Github user orhankislal closed the pull request at:
https://github.com/apache/incubator-madlib/pull/24
> Proportion of variance for PCA training function
> ------------------------------------------------
>
> Key: MADLIB-948
> URL: https://issues.apache.org/jira/browse/MADLIB-948
> Project: Apache MADlib
> Issue Type: New Feature
> Reporter: Frank McQuillan
> Priority: Minor
> Fix For: v2.0
>
>
> In future iterations of the pca_train command, is it feasible to insert
> another optional command called variance_proportion? Instead of specifying k
> principal components to compute, you instead specify the proportion of
> variance that you want your PCA vectors to account for. The number of
> principal vectors generated would depend the covariance matrix/correlation
> matrix (depending on whether you normalized or not) and variance_proportion.
> So if I specified that variance_proportion = .8, the algorithm would
> terminate after obtaining enough principal vectors so that the ratio of the
> sum of the eigenvalues collected thus far to the trace of the covariance
> matrix/correlation matrix (the sum of all of the eigenvalues of the
> covariance matrix/correlation matrix) is greater than or equal to .8. That
> is, the algorithm would terminate after collecting enough vectors to account
> for 80% of the total variance in the set of observations.
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