trainTestSplit: Split your data into a training and testing set
In amanda-park/easytidymodels: Make tidymodels even easier to run!

Description Usage Arguments Value Examples

Create a training and testing data set. Also returns a bootstrapped version of the training data set.

trainTestSplit(
  data = df,
  splitAmt = 0.8,
  timeDependent = FALSE,
  responseVar = "nameOfResponseVar",
  stratifyOnResponse = FALSE,
  numberOfBootstrapSamples = 25
)

`data`	The data set of interest.
`splitAmt`	The amount of data you want in the training set. Default is .8
`timeDependent`	Logical. Is your data time-dependent? If so, set TRUE.
`responseVar`	Name of response variable in analysis.
`stratifyOnResponse`	Logical. Should the training and testing splits be stratified based on the response? If so, set TRUE.
`numberOfBootstrapSamples`	Numeric. How many bootstrap samples do you want? Default is 25.

A list with four components: train is the training set, test is the testing set, boot is a bootstrapped data set, and split is an rsample object that helps split your original data set.

library(easytidymodels)
library(dplyr)
utils::data(penguins, package = "modeldata")
resp <- "sex"
split <- trainTestSplit(penguins, stratifyOnResponse = TRUE, responseVar = resp)
#Training data
split$train

#Testing data
split$test

#Bootstrapped data
split$boot

#Split object (helpful to call if you want to do model stacking)
split$split