Re: What is the most efficient and scalable way to get all the recommendation results from ALS model ?

+1 On Mar 21, 2016 09:52, "Hiroyuki Yamada" wrote: > Could anyone give me some advices or recommendations or usual ways to do > this ? > > I am trying to get all (probably top 100) product recommendations for each > user from a model (MatrixFactorizationModel), > but I

Re: What is the most efficient and scalable way to get all the recommendation results from ALS model ?

Could anyone give me some advices or recommendations or usual ways to do this ? I am trying to get all (probably top 100) product recommendations for each user from a model (MatrixFactorizationModel), but I haven't figured out yet to do it efficiently. So far, calling predict (predictAll in

What is the most efficient and scalable way to get all the recommendation results from ALS model ?

Hi, I'm testing Collaborative Filtering with Milib. Making a model by ALS.trainImplicit (or train) seems scalable as far as I have tested, but I'm wondering how I can get all the recommendation results efficiently. The predictAll method can get all the results, but it needs the whole