`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)
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`
An `rset` object that can be used with the `training` and `testing` functions to extract the data in each split.
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.
set.seed(1353) car_split <- initial_split(mtcars) train_data <- training(car_split) test_data <- testing(car_split)