Do recommendations and predictions based on SVD matrix factorization.
Recommendation is done based on folding-in. The strategy is do a fold-in
operation as described in
Sarwar et al., 2002 with the
baseline - The baseline scorer. Be very careful when configuring a different baseline
at runtime than at model-build time; such a configuration is unlikely to
rule - The update rule, or null (the default) to only use the user features
from the model. If provided, this update rule is used to update a user's
feature values based on their profile when scores are requested.
Score items in a vector. The key domain of the provided vector is the
items to score, and the score method sets the values for each item to
its score (or unsets it, if no score can be provided). The previous
values are discarded.