GitHub user iyerr3 opened a pull request:
https://github.com/apache/incubator-madlib/pull/48
SVM: Novelty detection using 1-class SVM
Jira: MADLIB-990
Additional author: Nandish Jayaram <[email protected]>
In this implementation of a one-class SVM, we are piggy-backing on the
existing
SVM classification. The input table to a one-class SVM does not require a
dependent variable. A maximum-margin classifier is learned that separates
all
the data from the origin. The default kernel for one-class is Gaussian
(rbf).
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/iyerr3/incubator-madlib feature/svm_one_class
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-madlib/pull/48.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 #48
----
commit c4211cef7043081852e1346218e81a78800a7428
Author: Rahul Iyer <[email protected]>
Date: 2016-04-21T18:38:28Z
SVM: Novelty detection using 1-class SVM
Jira: MADLIB-990
Additional author: Nandish Jayaram <[email protected]>
In this implementation of a one-class SVM, we are piggy-backing on the
existing
SVM classification. The input table to a one-class SVM does not require a
dependent variable. A maximum-margin classifier is learned that separates
all
the data from the origin. The default kernel for one-class is Gaussian
(rbf).
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