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Posted to issues@madlib.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2016/02/23 07:47:18 UTC
[jira] [Commented] (MADLIB-938) Non-linear SVM - polynomial kernel
[ https://issues.apache.org/jira/browse/MADLIB-938?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15158402#comment-15158402 ]
ASF GitHub Bot commented on MADLIB-938:
---------------------------------------
GitHub user mktal opened a pull request:
https://github.com/apache/incubator-madlib/pull/22
SVM: Add Polynomial Kernel
JIRA: MADLIB-938
The features are transformed using Kar and Karnick's appoach, which applies to any positive definite
kernel where the kernel function admits a Maclaurin expansion. This commit implements the special case
when the kernel function is polynomial.
@orhankislal Please review and comment
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mktal/incubator-madlib feature/svm_poly
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-madlib/pull/22.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 #22
----
commit b1d6c642fc37a353adefd9bb728a20e68ea16621
Author: Xiaocheng Tang <xi...@gmail.com>
Date: 2015-12-22T20:36:23Z
SVM: Add Polynomial Kernel
JIRA: MADLIB-938
The features are transformed using Kar and Karnick's appoach, which applies to any positive definite
kernel where the kernel function admits a Maclaurin expansion. This commit implements the special case
when the kernel function is polynomial.
----
> Non-linear SVM - polynomial kernel
> ----------------------------------
>
> Key: MADLIB-938
> URL: https://issues.apache.org/jira/browse/MADLIB-938
> Project: Apache MADlib
> Issue Type: New Feature
> Components: Module: Support Vector Machines
> Reporter: Frank McQuillan
> Assignee: Xiaocheng Tang
> Fix For: v1.9
>
>
> Story
> As a MADlib developer, I want to implement a polynomial kernel in the SVM algorithm, so that I get better classification/regression results for certain types of data sets.
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