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Posted to dev@madlib.apache.org by orhankislal <gi...@git.apache.org> on 2016/02/17 19:22:23 UTC
[GitHub] incubator-madlib pull request: PCA: Proportion of variance for PCA...
GitHub user orhankislal opened a pull request:
https://github.com/apache/incubator-madlib/pull/17
PCA: Proportion of variance for PCA training function
JIRA: MADLIB-948
- Added a new functionality where the user can specify the proportion of variance to be covered by the principal components. This function does not take an integer k value, instead a float value (between 0 and 1) is accepted.
- The interface has been updated with new parameter names to reflect the change.
- The sparse and block variants of PCA are updated to employ this functionality.
- The proportion of variance covered by each principal component is added to the output for the new function as well as the old one.
- The implementation required splitting the SVD function into two parts and applying various levels of wrappers so that the general SVD interface does not change while giving PCA enough access to manipulate the intermediate tables.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/orhankislal/incubator-madlib func/pca_prop
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-madlib/pull/17.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #17
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commit efa96cb43344aed29815dbcfb93d10be212f1a7e
Author: Orhan Kislal <ok...@pivotal.io>
Date: 2016-02-17T18:11:52Z
PCA: Proportion of variance for PCA training function
JIRA: MADLIB-948
- Added a new functionality where the user can specify the proportion of variance to be covered by the principal components. This function does not take an integer k value, instead a float value (between 0 and 1) is accepted.
- The interface has been updated with new parameter names to reflect the change.
- The sparse and block variants of PCA are updated to employ this functionality.
- The proportion of variance covered by each principal component is added to the output for the new function as well as the old one.
- The implementation required splitting the SVD function into two parts and applying various levels of wrappers so that the general SVD interface does not change while giving PCA enough access to manipulate the intermediate tables.
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[GitHub] incubator-madlib pull request: PCA: Proportion of variance for PCA...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/incubator-madlib/pull/17
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