R: Simple Training/Test Set Splitting

initial_split {rsample} | R Documentation

## Simple Training/Test Set Splitting

### Description

'initial_split' creates a single binary split of the data into a training set and testing set. 'training' and 'testing' are used to extract the resulting data.

### Usage

    initial_split(data, prop = 3/4, strata = NULL, ...)

    training(x)

    testing(x)

### Arguments

`data` | A data frame.
`prop` | The proportion of data to be retained for modeling/analysis.
`strata` | A variable that is used to conduct stratified sampling to create the resamples.
`...` | Not currently used.
`x` | An 'rsplit' object produced by 'initial_split'

### Details

The 'strata' argument causes the random sampling to be conducted *within the stratification variable*. The can help ensure that the number of data points in the training data is equivalent to the proportions in the original data set.

### Value

An 'rset' object that can be used with the 'training' and 'testing' functions to extract the data in each split.

### Examples

    set.seed(1353)
    car_split <- mc_cv(mtcars)
    train_data <- training(car_split)
    test_data <- testing(car_split)

[Package rsample version 0.0.2 Index]