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.

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

training(x)

testing(x)

## Arguments

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

## Value

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

## Examples

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