Thank you very much. I've read this tutorial, and understand what they've done. However, the ranks set, or number of iterations set is human defined, we can not sure the optimal value is in these set. By the way, I may expect or do some wrong thing, should find the best model.
On Wed, Aug 13, 2014 at 1:26 PM, Xiangrui Meng <men...@gmail.com> wrote: > You can define an evaluation metric first and then use a grid search > to find the best set of training parameters. Ampcamp has a tutorial > showing how to do this for ALS: > > http://ampcamp.berkeley.edu/big-data-mini-course/movie-recommendation-with-mllib.html > -Xiangrui > > On Tue, Aug 12, 2014 at 8:01 PM, Hoai-Thu Vuong <thuv...@gmail.com> wrote: > > In MLLib, I found the method to train matrix factorization model to > predict > > the taste of user. In this function, there are some parameters such as > > lambda, and rank, I can not find the best value to set these parameters > and > > how to optimize this value. Could you please give me some recommends? > > > > -- > > Thu. > -- Thu.
