[jira] Commented: (MAHOUT-85) Perceptron/Winnow Trainer

["Kay Kay (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MAHOUT-85?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12658860#action_12658860 ] 

Kay Kay commented on MAHOUT-85:
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Would it be better to add another ctor. with the distance measure as a configurable parameter (with cosine being retained as the default measure ). 

Also - regarding LinearModel ( member: Vector and methods: add (Vector delta) , timesDelta(Vector delta)  ) - can having additional abstraction of a HyperPlane (with Vector as members and addDelta / timesDelta  / distance as methods to it ).  That might be more cleaner , since theoretically we define a LinearModel to be a HyperPlane with a specific DistanceMeasure  and perform classification on the same, and adding / scaling the hyperplane vector is better consolidated separately as opposed to the LinearModel itself. 




> Perceptron/Winnow Trainer
> -------------------------
>
>                 Key: MAHOUT-85
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-85
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Classification
>            Reporter: Isabel Drost
>            Assignee: Isabel Drost
>         Attachments: perceptronWinnowTrainer.diff
>
>
> Please find attached a first sketch for perceptron and winnow training. Please look very, very carefully at the patch, as I added the heart of the algorithms in the emergency room at Charite Berlin (after I broke my leg when cycling to the Hadoop Get Together ;) ). 
> The patch does not yet feature unit tests nor is it parallelised. Currently my plan is to set up an example with the webKb dataset, add unit tests to the code and after that go parallel. I would like to get some feedback early on, in addition I would feel a lot better, if a second and third pair of eyes had a look at the code to make sure all obvious mistakes are out as early as possible.

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