R: Creates cross-validation set from user-item interactions

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 `Matrix::TsparseMatrix` is used.
`test_proportion` | - proportion of the observations for each user to keep as "test" data.

[Package rsparse version 0.4.0 Index]