Yes -- though I might use more like 95% for training. You aren't running recommendations, quite; you're computing estimated prefs, which is the step before recommendation. I assume you're doing a RMSE comparison?
2011/10/17 WangRamon <[email protected]>: > > Hi Sean Do you mean that I should take the concept from the standalone one, > keep some real data, let's say 20% of all data, do recommend computation on > the other 80%, and finally do a comparation. CheersRamon > > Date: Mon, 17 Oct 2011 08:02:37 +0100 >> Subject: Re: Does Mahout provide a way to evaluate a distributed Recommender >> running on Hadoop? >> From: [email protected] >> To: [email protected] >> >> There is not one, though you could probably adapt the evaluation code >> without a great deal of trouble. The concept is the same; the >> implementation is quite different. You would withhold some data, and >> then compute the value of that withheld data and compare with the >> original. >> >> 2011/10/17 WangRamon <[email protected]>: >> > >> > >> > >> > >> > Hi Guys >> > >> > We're going to evaluate how good a distributed (on Hadoop) recommender is, >> > i found Mahout provides some stand alone implementation to evaluate a >> > recommender, so is there a distributed implementation we can use in a >> > Hadoop environment, thanks a lot. >> > >> > BTW, if there is not such an implementation, do we have any solution/idea >> > on how to implement one? >> > >> > Cheers >> > Ramon >
