This package implements the methods for providing sufficient representations of categorical variables mentioned in Johannemann et al. (2019).
To install this package, run the following commands in R:
library(devtools)
install_github("grf-labs/sufrep")Example usage:
library(sufrep)
set.seed(12345)
n <- 100
p <- 3
X <- matrix(rnorm(n * p), n, p)
G <- as.factor(sample(5, size = n, replace = TRUE))
# One-hot encoding
onehot_encoder <- make_encoder(X = X, G = G, method = "one_hot")
train.df <- onehot_encoder(X = X, G = G)
print(head(train.df))
# [,1] [,2] [,3] [,4] [,5] [,6] [,7]
# [1,] 0.5855 0.2239 -1.4361 0 0 0 1
# [2,] 0.7095 -1.1562 -0.6293 1 0 0 0
# [3,] -0.1093 0.4224 0.2435 0 0 1 0
# [4,] -0.4535 -1.3248 1.0584 0 0 0 1
# [5,] 0.6059 0.1411 0.8313 0 1 0 0
# [6,] -1.8180 -0.5360 0.1052 0 0 0 0
# "Means" encoding
means_encoder <- make_encoder(X = X, G = G, method = "means")
train.df <- means_encoder(X = X, G = G)
print(head(train.df))
# [,1] [,2] [,3] [,4] [,5] [,6]
# [1,] 0.5855 0.2239 -1.4361 0.1464 0.014645 -0.21528
# [2,] 0.7095 -1.1562 -0.6293 0.1892 0.177011 0.03227
# [3,] -0.1093 0.4224 0.2435 -0.3276 -0.009544 0.06307
# [4,] -0.4535 -1.3248 1.0584 0.1464 0.014645 -0.21528
# [5,] 0.6059 0.1411 0.8313 0.4915 0.159208 0.17173
# [6,] -1.8180 -0.5360 0.1052 0.5474 -0.056997 -0.16276Jonathan Johannemann, Vitor Hadad, Susan Athey, and Stefan Wager. Sufficient Representations of Categorical Variables. 2019.