recosystem (version 0.5.1)

output: Exporting Factorization Matrices

Description

This method is a member function of class "RecoSys" that exports the user score matrix \(P\) and the item score matrix \(Q\).

Prior to calling this method, model needs to be trained using member function $train().

The common usage of this method is

r = Reco()
r$train(...)
r$output(out_P = out_file("mat_P.txt"), out_Q = out_file("mat_Q.txt"))

Value

A list with components P and Q. They will be filled with user or item matrix if out_memory() is used in the function argument, otherwise NULL will be returned.

Arguments

r

Object returned by Reco().

out_P

An object of class Output that specifies the output format of the user matrix, typically returned by function out_file(), out_memory() or out_nothing(). out_file() writes the matrix into a file, with each row representing a user and each column representing a latent factor. out_memory() exports the matrix into the return value of $output(). out_nothing() means the matrix will not be exported.

out_Q

Ditto, but for the item matrix.

Author

Yixuan Qiu <https://statr.me>

References

W.-S. Chin, Y. Zhuang, Y.-C. Juan, and C.-J. Lin. A Fast Parallel Stochastic Gradient Method for Matrix Factorization in Shared Memory Systems. ACM TIST, 2015.

W.-S. Chin, Y. Zhuang, Y.-C. Juan, and C.-J. Lin. A Learning-rate Schedule for Stochastic Gradient Methods to Matrix Factorization. PAKDD, 2015.

W.-S. Chin, B.-W. Yuan, M.-Y. Yang, Y. Zhuang, Y.-C. Juan, and C.-J. Lin. LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems. Technical report, 2015.

See Also

$train(), $predict()

Examples

train_set = system.file("dat", "smalltrain.txt", package = "recosystem")
r = Reco()
set.seed(123) # This is a randomized algorithm
r$train(data_file(train_set), out_model = file.path(tempdir(), "model.txt"),
        opts = list(dim = 10, nmf = TRUE))

## Write P and Q matrices to files
P_file = out_file(tempfile())
Q_file = out_file(tempfile())
r$output(P_file, Q_file)
head(read.table(P_file@dest, header = FALSE, sep = " "))
head(read.table(Q_file@dest, header = FALSE, sep = " "))

## Skip P and only export Q
r$output(out_nothing(), Q_file)

## Return P and Q in memory
res = r$output(out_memory(), out_memory())
head(res$P)
head(res$Q)