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From Reza Zadeh <r...@databricks.com>
Subject Re: Is it possible to do incremental training using ALSModel (MLlib)?
Date Sat, 03 Jan 2015 05:04:29 GMT
There is a JIRA for it: https://issues.apache.org/jira/browse/SPARK-4981

On Fri, Jan 2, 2015 at 8:28 PM, Peng Cheng <rhwing@gmail.com> wrote:

> I was under the impression that ALS wasn't designed for it :-< The famous
> ebay online recommender uses SGD
> However, you can try using the previous model as starting point, and
> gradually reduce the number of iteration after the model stablize. I never
> verify this idea, so you need to at least cross-validate it before putting
> into productio
>
> On 2 January 2015 at 04:40, Wouter Samaey <wouter.samaey@storefront.be>
> wrote:
>
>> Hi all,
>>
>> I'm curious about MLlib and if it is possible to do incremental training
>> on
>> the ALSModel.
>>
>> Usually training is run first, and then you can query. But in my case,
>> data
>> is collected in real-time and I want the predictions of my ALSModel to
>> consider the latest data without complete re-training phase.
>>
>> I've checked out these resources, but could not find any info on how to
>> solve this:
>> https://spark.apache.org/docs/latest/mllib-collaborative-filtering.html
>>
>> http://ampcamp.berkeley.edu/big-data-mini-course/movie-recommendation-with-mllib.html
>>
>> My question fits in a larger picture where I'm using Prediction IO, and
>> this
>> in turn is based on Spark.
>>
>> Thanks in advance for any advice!
>>
>> Wouter
>>
>>
>>
>> --
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>>
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>

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