train_test_split {rsparse} | R Documentation |
Creates cross-validation set from user-item interactions
Description
Basic splitting of the user-item interaction matrix into train and testing part.
Useful for when data doesn't have time dimension.
Usually during model tuning it worth to keep some x
matrix as hold-out data set.
Then this x
could be splitted in 2 parts - train and test.
Model tries to predict test data using train
Usage
train_test_split(x, test_proportion = 0.5)
Arguments
x |
sparse user-item interation matrix. Internally |
test_proportion |
- proportion of the observations for each user to keep as "test" data. |
[Package rsparse version 0.5.2 Index]