@erikcs @halflearned
it seems that the make_encoder() function only allow for one categorical variable at a time. As an example, the code below produces error. Could be a nice improvement to allow for multiple categorical variables or just to type in the code to use in this case.
library(sufrep)
set.seed(12345)
n <- 100
p <- 3
X <- matrix(rnorm(n * p), n, p)
G <- data.frame(as.factor(sample(5, size = n, replace = TRUE)), 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))
@erikcs @halflearned
it seems that the make_encoder() function only allow for one categorical variable at a time. As an example, the code below produces error. Could be a nice improvement to allow for multiple categorical variables or just to type in the code to use in this case.
library(sufrep)
set.seed(12345)
n <- 100
p <- 3
X <- matrix(rnorm(n * p), n, p)
G <- data.frame(as.factor(sample(5, size = n, replace = TRUE)), 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))