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From "Hector Yee (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (MAHOUT-703) Implement Gradient machine
Date Sat, 21 May 2011 08:52:47 GMT

     [ https://issues.apache.org/jira/browse/MAHOUT-703?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Hector Yee updated MAHOUT-703:
------------------------------

    Attachment: MAHOUT-703.patch

Working ranking neural net, less the sparsity enforcing part. Would appreciate if someone
could check the math. Unit tests pass.

> Implement Gradient machine
> --------------------------
>
>                 Key: MAHOUT-703
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-703
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Classification
>    Affects Versions: 0.6
>            Reporter: Hector Yee
>            Priority: Minor
>              Labels: features
>             Fix For: 0.6
>
>         Attachments: MAHOUT-703.patch
>
>   Original Estimate: 72h
>  Remaining Estimate: 72h
>
> Implement a gradient machine (aka 'neural network) that can be used for classification
or auto-encoding.
> It will just have an input layer, identity, sigmoid or tanh hidden layer and an output
layer.
> Training done by stochastic gradient descent (possibly mini-batch later).
> Sparsity will be optionally enforced by tweaking the bias in the hidden unit.
> For now it will go in classifier/sgd and the auto-encoder will wrap it in the filter
unit later on.

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