calc.all.counts | Predict whole input matrix |
evaluate.poisson.llk | Evaluate Poisson log-likelihood for counts matrix |
factors | Determine latent factors for new rows/users |
factors.single | Get latent factors for a new user given her item counts |
get.factor.matrices | Extract Latent Factor Matrices |
get.model.mappings | Extract user/row and item/column mappings from Poisson model. |
poismf | Factorization of Sparse Counts Matrices through Poisson Likelihood |
poismf_unsafe | Poisson factorization with no input casting |
predict.poismf | Predict expected count for new row(user) and column(item) combinations |
print.poismf | Get information about poismf object |
summary.poismf | Get information about poismf object |
topN | Rank top-N highest-predicted items for an existing user |
topN.new | Rank top-N highest-predicted items for a new user |