Convert a vector of unordered categorical data (either numeric or character labels) to a "one-hot" encoded matrix in which a 1 in a column indicates the presence of the relevant category.

This procedure assumes that a reference set of observations for this variable (typically a training set that was used to sample a forest) has already been one-hot encoded and that the unique levels of the training set variable are available (and passed as unique_levels). Test set observations that contain categories not in unique_levels will all be mapped to the last column of this matrix

Usage

oneHotEncode(x_input, unique_levels)

Arguments

x_input

Vector of unordered categorical data (typically either strings integers, but this function also accepts floating point data).

unique_levels

Unique values of the categorical variable used to create the initial one-hot matrix (typically a training set)

Value

Binary one-hot matrix

Examples

x <- sample(1:8, 100, TRUE)
x_test <- sample(1:9, 10, TRUE)
x_onehot <- oneHotEncode(x_test, levels(factor(x)))