How to one hot encode several categorical variables in R

Question

I\'m working on a prediction problem and I\'m building a decision tree in R, I have several categorical variables and I\'d like to one-hot encode them consistently in my tra

Answer 1

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.

Example

Here's an example using the iris dataset.

data(iris)
#Split into train and test sets.
train <- sample(1:nrow(iris),100)
test <- -1*train

iris[test,]

    Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
34           5.5         4.2          1.4         0.2    setosa
106          7.6         3.0          6.6         2.1 virginica
112          6.4         2.7          5.3         1.9 virginica
127          6.2         2.8          4.8         1.8 virginica
132          7.9         3.8          6.4         2.0 virginica

model.matrix() creates a column for each level of the factor, even if it is not present in the data. Zero indicates it is not that level, one indicates it is. Adding the zero specifies that you do not want an intercept or reference level and is equivalent to -1.

oh_train <- model.matrix(~0+iris[train,'Species'])
oh_test <- model.matrix(~0+iris[test,'Species'])

#Renaming the columns to be more concise.
attr(oh_test, "dimnames")[[2]] <- levels(iris$Species)


  setosa versicolor virginica
1      1          0         0
2      0          0         1
3      0          0         1
4      0          0         1
5      0          0         1

P.S. It's generally preferable to include all categories in training and test data. But that's none of my business.