Extract the latent factor matrices for users (rows) and columns (items) from a Poisson factorization model object, as returned by function 'poismf'.
A Poisson factorization model, as produced by 'poismf'.
Whether to add row names to the matrices if the indices were internally remapped - they will only be so if the 'X' passed to 'poismf' was a 'data.frame'. Note that if passing 'X' as 'data.frame' with integer indices to 'poismf', once row names are added, subsetting such matrix by an integer will give the row at that position - that is, if you want to obtain the corresponding row for ID=2 from 'X' in 'factors$A', you need to use 'factors$A["2", ]', not 'factors$A[2, ]'.
If 'X' passed to 'poismf' was a 'data.frame', the mapping between IDs from 'X' to row numbers in 'A' and column numbers in 'B' are avaiable under 'model$levels_A' and 'model$levels_B', respectively. They can also be obtained through 'get.model.mappings', and will be added as row names if using 'add_names=TRUE'. Be careful about subsetting with integers (see documentation for 'add_names' for details).
List with entries 'A' (the user factors) and 'B' (the item factors).
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.