GitHub user mktal opened a pull request:
https://github.com/apache/incubator-madlib/pull/75
SVM: Implement c++ functions for training multi-class svm in mini-batch
This PR implements multi-class support vector machine and a new training
mechanism using buffered mini-batch stochastic gradient descent (hence
"in-memory" computations across epochs). Preliminary experiments demonstrate
potential on greatly improving training speed and accuracy in MADlib. For
example, training on mnist datasets (10 classes) for **1s** on HAWQ half-rack
DCA and the model is able to achieve over **90% accuracy** on holdout data. The
training and testing set in this case consist of 46900 and 23100 images,
respectively.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mktal/incubator-madlib feature/svm_multi_class
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-madlib/pull/75.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 #75
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commit 85b985cc8b52839a7d5a00afd8dfb6e81180e656
Author: Xiaocheng Tang <[email protected]>
Date: 2016-11-14T20:56:42Z
SVM: Implement c++ functions for training multi-class svm in mini-batch
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