How to One Hot Encode Several Categorical Variables in R

I recommend using the dummyVars function in the caret package:

library(caret)

customers <- data.frame(
  id=c(10, 20, 30, 40, 50),
  gender=c('male', 'female', 'female', 'male', 'female'),
  mood=c('happy', 'sad', 'happy', 'sad','happy'),
  outcome=c(1, 1, 0, 0, 0))
customers
id gender  mood outcome
1 10   male happy       1
2 20 female   sad       1
3 30 female happy       0
4 40   male   sad       0
5 50 female happy       0


# dummify the data
dmy <- dummyVars(" ~ .", data = customers)
trsf <- data.frame(predict(dmy, newdata = customers))
trsf
id gender.female gender.male mood.happy mood.sad outcome
1 10             0           1          1        0       1
2 20             1           0          0        1       1
3 30             1           0          1        0       0
4 40             0           1          0        1       0
5 50             1           0          1        0       0

example source

You apply the same procedure to both the training and validation sets.

Here's a simple solution to one-hot-encode your category using no packages.

Solution

model.matrix(~0+category)

It needs your categorical variable to be a factor. The factor levels must be the same in your training and test data, check with levels(train$category) and levels(test$category). It doesn't matter if some levels don't occur in your test set.