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Posted to dev@hama.apache.org by "Hudson (JIRA)" <ji...@apache.org> on 2013/08/07 06:43:48 UTC
[jira] [Commented] (HAMA-791) Fix the problem that
MultilayerPerceptron fails to learn a good hypothesis sometimes
[ https://issues.apache.org/jira/browse/HAMA-791?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13731629#comment-13731629 ]
Hudson commented on HAMA-791:
-----------------------------
SUCCESS: Integrated in Hama trunk #152 (See [https://builds.apache.org/job/Hama%20trunk/152/])
HAMA-791: Fix the problem that MultilayerPerceptron fails to learn a good hypothesis sometimes (yxjiang: rev 1511164)
* /hama/trunk/CHANGES.txt
* /hama/trunk/ml/src/test/java/org/apache/hama/ml/perception/TestSmallMultiLayerPerceptron.java
> Fix the problem that MultilayerPerceptron fails to learn a good hypothesis sometimes
> ------------------------------------------------------------------------------------
>
> Key: HAMA-791
> URL: https://issues.apache.org/jira/browse/HAMA-791
> Project: Hama
> Issue Type: Bug
> Reporter: Yexi Jiang
> Assignee: Yexi Jiang
> Labels: machine_learning
> Fix For: 0.6.3
>
> Attachments: HAMA-791.patch
>
>
> Fix the problem that MultilayerPerceptron fails to learn a good hypothesis sometimes. If the weights of MLP initialized to very bad values, the model might fail the test.
> Since the new model developed in [HAMA-770|https://issues.apache.org/jira/browse/HAMA-770] will replace the current old model, this problem will be simply fixed by increase the training iteration.
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