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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

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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)
Edit and Run Code