Prep and split
You will be working with the full attrition
dataset with 1470 instances of 30 features related to the target variable Attrition
, including missing values. The mission is to build a full end-to-end model to predict your target. The dataset is loaded for you.
You'll start by preparing and splitting the data.
This exercise is part of the course
Feature Engineering in R
Exercise instructions
- Begin by transforming all character values to factors.
- Create train and test splits.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Transform all character values to factors
attrition <-
attrition %>%
mutate(___(where(___), as_factor))
# Create train and test splits
set.seed(123)
split <- initial_split(attrition, strata = Attrition)
test <- ___(split)
train <- ___(___)
glimpse(train)