Hi Sean, Neither Recommender nor any of its parent interface extends serializable so there is no way that I'd be able to serialize it.
I agree that the implementations may not have startup overhead. However, training a model on millions of row is a cpu, memory & time consuming activity. For example, when data set is changed from 100K to 1M in chapter 4, program crashes with OutOfMemory after significant amount of time. I feel that training should be done in development only. Once a developer is ok with test results, he should be able to save instance of the trained and tested model (for ex:- recommender or classifier). These saved instances of trained and tested models only should be deployed to production. Thought? regards, Vinod On Thu, Dec 8, 2011 at 6:00 PM, Sean Owen <[email protected]> wrote: > Ah right. No, there's still not a provision for this. You would just have > to serialize it yourself if you like. > Most of the implementations don't have a great deal of startup overhead, so > don't really need this. The exception is perhaps slope-one, but there you > can actually save and supply pre-computed diffs. > Still it would be valid to store and re-supply user-user similarities or > something. You can do this, manually, by querying for user-user > similarities, saving them, then loading them and supplying them via > GenericUserSimilarity for instance. > > On Thu, Dec 8, 2011 at 12:27 PM, Vinod <[email protected]> wrote: > > > Hi Sean, > > > > Thanks for the quick response. > > > > By model, I am not referring to data model but, a "trained" recommender > > instance. > > > > Weka, for examples, has ability to save and load models:- > > http://weka.wikispaces.com/Serialization > > http://weka.wikispaces.com/Saving+and+loading+models > > > > This avoids the need to train model (recommender) every time a server is > > bounced or program is restarted. > > > > regards, > > Vinod > > > > > > On Thu, Dec 8, 2011 at 5:43 PM, Sean Owen <[email protected]> wrote: > > > > > The classes aren't Serializable, no. In the case of DataModel, it's > > assumed > > > that you already have some persisted model somewhere, in a DB or file > or > > > something, so this would be redundant. > > > > > > On Thu, Dec 8, 2011 at 12:07 PM, Vinod <[email protected]> wrote: > > > > > > > Hi, > > > > > > > > This is my first day of experimentation with Mahout. I am following > > > "Mahout > > > > in Action" book and looking at the sample code provided, it seems > that > > > > models for ex:- recommender, needs to be trained at the start of the > > > > program (start/restart). Recommender interface extends Refreshable > > which > > > > doesn't extend serializable. So, I am wondering if Mahout provides an > > > > alternate mechanism to to persist trained models (recommender > instance > > in > > > > this case). > > > > > > > > Apologies if this is a very silly question. > > > > > > > > Thanks & regards, > > > > Vinod > > > > > > > > > >
