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Hive >> mail # user >> [ANN] Hivemall: Hive scalable machine learning library


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Re: [ANN] Hivemall: Hive scalable machine learning library
Just tried this for some hot trends in forum managements. Was pretty
impressive.

I will try this more deeply and if possible integrate in my product.

Thanks for the awesome work.

Nitin
On Fri, Oct 11, 2013 at 12:58 PM, Makoto YUI <[EMAIL PROTECTED]> wrote:

> Hi,
>
> I added support for the-state-of-the-art classifiers (those are not yet
> supported in Mahout) and Hivemall's cute(!?) logo as well in Hivemall
> 0.1-rc3.
>
> Newly supported classifiers include
> - Confidence Weighted (CW)
> - Adaptive Regularization of Weight Vectors (AROW)
> - Soft Confidence Weighted (SCW1, SCW2)
>
> Those classifiers are much smart comparing to the standard SGD-based or
> passive aggressive classifiers. Please check it out by yourself.
>
> Thanks,
> Makoto
>
>
> (2013/10/11 4:28), Clark Yang (杨卓荦) wrote:
>
>> I looks really cool, I think I will try it on.
>>
>> Cheers,
>> Zhuoluo (Clark) Yang
>>
>>
>> 2013/10/5 Makoto YUI <[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>>
>>
>>
>>     Hi Edward,
>>
>>     Thank you for your interst.
>>
>>     Hivemall project does not have a plan to have a specific mailing
>>     list, I will answer following questions/comments on twitter or
>>     through Github issues (with a question label).
>>
>>     BTW, I just added a CTR (Click-Through-Rate) prediction example that
>> is
>>     provided by a commercial search engine provider for the KDDCup 2012
>>     track 2.
>>     https://github.com/myui/__**hivemall/wiki/KDDCup-2012-__**
>> track-2-CTR-prediction-dataset<https://github.com/myui/__hivemall/wiki/KDDCup-2012-__track-2-CTR-prediction-dataset>
>>
>>     <https://github.com/myui/**hivemall/wiki/KDDCup-2012-**
>> track-2-CTR-prediction-dataset<https://github.com/myui/hivemall/wiki/KDDCup-2012-track-2-CTR-prediction-dataset>
>> **>
>>
>>     I guess many of you working on ad CTR/CVR predictions. This example
>>     might be some help understanding how to do it only within Hive.
>>
>>     Thanks,
>>     Makoto @myui
>>
>>
>>     (2013/10/04 23:02), Edward Capriolo wrote:
>>
>>         Looks cool im already starting to play with it.
>>
>>         On Friday, October 4, 2013, Makoto Yui <[EMAIL PROTECTED]
>>         <mailto:[EMAIL PROTECTED]>
>>         <mailto:[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>>> wrote:
>>           > Hi Dean,
>>           >
>>           > Thank you for your interest in Hivemall.
>>           >
>>           > Twitter's paper actually influenced me in developing
>>         Hivemall and I
>>           > initially implemented such functionality as Pig UDFs.
>>           >
>>           > Though my Pig ML library is not released, you can find a
>> similar
>>           > attempt for Pig in
>>           > https://github.com/y-tag/java-**__pig-MyUDFs<https://github.com/y-tag/java-__pig-MyUDFs>
>>
>>         <https://github.com/y-tag/**java-pig-MyUDFs<https://github.com/y-tag/java-pig-MyUDFs>
>> >
>>           >
>>           > Thanks,
>>           > Makoto
>>           >
>>           > 2013/10/3 Dean Wampler <[EMAIL PROTECTED]
>>         <mailto:[EMAIL PROTECTED]>
>>         <mailto:[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>**
>> >__>:
>>
>>
>>           >> This is great news! I know that Twitter has done something
>>         similar
>>         with UDFs
>>           >> for Pig, as described in this paper:
>>           >>
>>         http://www.umiacs.umd.edu/~__**jimmylin/publications/Lin___**
>> Kolcz_SIGMOD2012.pdf<http://www.umiacs.umd.edu/~__jimmylin/publications/Lin___Kolcz_SIGMOD2012.pdf>
>>         <http://www.umiacs.umd.edu/%**7Ejimmylin/publications/Lin_**
>> Kolcz_SIGMOD2012.pdf<http://www.umiacs.umd.edu/%7Ejimmylin/publications/Lin_Kolcz_SIGMOD2012.pdf>
>> >
>>         <http://www.umiacs.umd.edu/%__**7Ejimmylin/publications/Lin___**
>> Kolcz_SIGMOD2012.pdf
>>
>>         <http://www.umiacs.umd.edu/%**7Ejimmylin/publications/Lin_**
>> Kolcz_SIGMOD2012.pdf<http://www.umiacs.umd.edu/%7Ejimmylin/publications/Lin_Kolcz_SIGMOD2012.pdf>
>> >>
>>
>>           >>
>>           >> I'm glad to see the same thing start with Hive.
Nitin Pawar
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB