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From Xiangrui Meng <men...@gmail.com>
Subject Re: Building Desktop application for ALS-MlLib/ Training ALS
Date Mon, 15 Dec 2014 20:04:50 GMT
On Sun, Dec 14, 2014 at 3:06 AM, Saurabh Agrawal
<saurabh.agrawal@markit.com> wrote:
>
>
> Hi,
>
>
>
> I am a new bee in spark and scala world
>
>
>
> I have been trying to implement Collaborative filtering using MlLib supplied
> out of the box with Spark and Scala
>
>
>
> I have 2 problems
>
>
>
> 1.       The best model was trained with rank = 20 and lambda = 5.0, and
> numIter = 10, and its RMSE on the test set is 25.718710831912485. The best
> model improves the baseline by 18.29%. Is there a scientific way in which
> RMSE could be brought down? What is a descent acceptable value for RMSE?
>

The grid search approach used in the AMPCamp tutorial is pretty
standard. Whether an RMSE is good or not really depends on your
dataset.

> 2.       I picked up the Collaborative filtering algorithm from
> http://ampcamp.berkeley.edu/5/exercises/movie-recommendation-with-mllib.html
> and executed the given code with my dataset. Now, I want to build a desktop
> application around it.
>
> a.       What is the best language to do this Java/ Scala? Any possibility
> to do this using C#?
>

We support Java/Scala/Python. Start with the one your are most
familiar with. C# is not supported.

> b.      Can somebody please share any relevant documents/ source or any
> helper links to help me get started on this?
>

For ALS, you can check the API documentation.

>
>
> Your help is greatly appreciated
>
>
>
> Thanks!!
>
>
>
> Regards,
>
> Saurabh Agrawal
>
>
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