spark-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Xiangrui Meng <men...@gmail.com>
Subject Re: MlLib Colaborative filtering factors
Date Tue, 25 Nov 2014 18:15:50 GMT
It is data-dependent, and hence needs hyper-parameter tuning, e.g.,
grid search. The first batch is certainly expensive. But after you
figure out a small range for each parameter that fits your data,
following batches should be not that expensive. There is an example
from AMPCamp: http://ampcamp.berkeley.edu/5/exercises/movie-recommendation-with-mllib.html
-Xiangrui

On Tue, Nov 25, 2014 at 4:28 AM, Saurabh Agrawal
<saurabh.agrawal@markit.com> wrote:
>
>
> HI,
>
>
>
> I am trying to execute Collaborative filtering using MlLib. Can somebody
> please suggest how to calculate the following
>
>
>
> 1.       Rank
>
> 2.       Iterations
>
> 3.       Lambda
>
>
>
> I understand these are adjustment factors and they help reduce the MSE in
> turn defining accuracy of algorithm but then is it all hit and trial or is
> there a definitive way to calculate them?
>
>
>
>
>
> Thanks!!
>
>
>
> Regards,
>
> Saurabh Agrawal
>
>
> ________________________________
> This e-mail, including accompanying communications and attachments, is
> strictly confidential and only for the intended recipient. Any retention,
> use or disclosure not expressly authorised by Markit is prohibited. This
> email is subject to all waivers and other terms at the following link:
> http://www.markit.com/en/about/legal/email-disclaimer.page
>
> Please visit http://www.markit.com/en/about/contact/contact-us.page? for
> contact information on our offices worldwide.
>
> MarkitSERV Limited has its registered office located at Level 4, Ropemaker
> Place, 25 Ropemaker Street, London, EC2Y 9LY and is authorized and regulated
> by the Financial Conduct Authority with registration number 207294

---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
For additional commands, e-mail: user-help@spark.apache.org


Mime
View raw message