Classifier based on restricted boltzmann machines
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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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