All matrix factorization recommenders inherit from this class
components
item embeddings
predict()
recommends items for users
MatrixFactorizationRecommender$predict( x, k, not_recommend = x, items_exclude = integer(0), ... )
x
user-item interactions matrix (usually sparse - `Matrix::sparseMatrix`).Users are rows and items are columns
k
number of items to recommend
not_recommend
user-item matrix (sparse) which describes which items method should NOT recomment for each user. Usually this is same as `x` as we don't want to recommend items user already liked.
items_exclude
either integer indices or character identifiers of the items to not recommend to any user.
...
not used at the moment
clone()
The objects of this class are cloneable with this method.
MatrixFactorizationRecommender$clone(deep = FALSE)
deep
Whether to make a deep clone.