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## 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.
