Functions in this page are used to specify the source of data in the recommender system.
They are intended to provide the input argument of functions such as
$tune()
, $train()
, and $predict()
.
Currently two data formats are supported: data file (via function data_file()
),
and data in memory as R objects (via function data_memory()
).
data_file(path, index1 = FALSE, ...)data_memory(user_index, item_index, rating = NULL, index1 = FALSE, ...)
Path to the data file.
Whether the user indices and item indices start with 1
(index1 = TRUE
) or 0 (index1 = FALSE
).
Currently unused.
An integer vector giving the user indices of rating scores.
An integer vector giving the item indices of rating scores.
A numeric vector of the observed entries in the rating matrix.
Can be specified as NULL
for testing data, in which case
it is ignored.
An object of class "DataSource" as required by
$tune()
, $train()
, and $predict()
.
In $tune()
and $train()
, functions in this page
are used to specify the source of training data. data_file()
expects a text file that describes a sparse matrix
in triplet form, i.e., each line in the file contains three numbers
row col value
representing a number in the rating matrix with its location. In real applications, it typically looks like
user_index item_index rating
The smalltrain.txt
file in the dat
directory of this package
shows an example of training data file.
From version 0.4 recosystem supports two special types of matrix factorization: the binary matrix factorization (BMF), and the one-class matrix factorization (OCMF). BMF requires ratings to take value from \({-1, 1}\), and OCMF requires all the ratings to be positive.
If user index, item index, and ratings are stored as R vectors in memory,
they can be passed to data_memory()
to form the training data source.
By default the user index and item index start with zeros, and the option
index1 = TRUE
can be set if they start with ones.
In $predict()
, functions in this page provide the source of
testing data. The testing data have the same format as training data, except
that the value (rating) column is not required, and will be ignored if it is
provided. The smalltest.txt
file in the dat
directory of this
package shows an example of testing data file.