## Predicting & recommending Once a model has been trained rrecsys may be used to generate either recommendation or predictions. The prediction method will generate a new rating matrix with estimations on the missing ratings. Let’s predict using two models trained in the previous vignettes: ```{r, eval=FALSE} pSVD <- predict(svd) pIB <- predict(ibknn) ``` The _predict_ method has a second argument, _Round_ that rounds predicted values to the scale and binds them to the domain of the data set. The _recommend_ method generates a top-N list for each user: ```{r, eval=FALSE} rSVD <- recommendHPR(svd, topN = 3) rIB <- recommendHPR(ibknn, topN = 3) # Let’s compare results on user 3: rSVD[4] rIB[4] ``` The _topN_ argument specifies the length of the recommended list for each user.