Dirk,

Can you provide some comparison with RBM's and the Bayesian learning
algorithm such as described here:
http://research.microsoft.com/apps/pubs/default.aspx?id=122779

On Wed, Feb 1, 2012 at 3:32 AM, Dirk Weißenborn (Created) (JIRA) <
[email protected]> wrote:

> Classifier based on restricted boltzmann machines
> -------------------------------------------------
>
>                 Key: MAHOUT-968
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-968
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Classification
>            Reporter: Dirk Weißenborn
>
>
> This is a proposal for a new classifier based on restricted boltzmann
> machines. The development of this feature follows the paper on "Deep
> Boltzmann Machines" (DBM) [1] from 2009. The proposed model (DBM) got an
> error rate of 0.95% on the mnist dataset [2], which is really good. Main
> parts of the implementation should also be applicable to other scenarios
> than classification where restricted boltzmann machines are used (ref.
> MAHOUT-375).
> I am working on this feature right now, and the results are promising. The
> only problem with the training algorithm is, that it is still mostly
> sequential (if training batches are small, what they should be), which
> makes Map/Reduce until now, not really beneficial. However, since the
> algorithm itself is fast (for a training algorithm), training can be done
> on a single machine in managable time.
> Testing of the algorithm is currently done on the mnist dataset itself to
> reproduce results of [1]. As soon as results indicate, that everything is
> working fine, I will upload the patch.
>
> [1] http://www.cs.toronto.edu/~hinton/absps/dbm.pdf
> [2] http://yann.lecun.com/exdb/mnist/
>
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