Для справки в будущем ответ с представителем, который использует то же решение, которое было предложено @Rorschach:
x <- runif(50, min = 0, max = 100)
z <- runif(50, min = 0, max = 100)
a <- runif(50, min = 0, max = 100)
b <- runif(50, min = 0, max = 100)
positive <- rbinom(50,1, 0.4)
training <- as.data.frame(cbind(x,z,a,b,positive = positive))
training$positive <- factor(training$positive)
library(caret)
features <- c("x","z","a","b")
out <- list()
for (f in features) {
mod <- train(form = as.formula(paste("positive ~ ", f)),
data = training,
method = "glm",
family = "binomial")
out <- append(out,mod)
}