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From Peng Cheng <rhw...@gmail.com>
Subject Re: Is it possible to do incremental training using ALSModel (MLlib)?
Date Sat, 03 Jan 2015 04:28:32 GMT
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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