循环中的简单逻辑回归？

Question

我有一系列用于多变量逻辑回归的特征，但我想分别测试多个单变量逻辑回归的每个特征。

我试着像这样做一个循环

features <- c("f1","f2","f3","f4")
out <- list()
for (f in features) {
    mod <- train(form = positive ~ f,
                 data = training,
                 method = "glm",
                 metric = "ROC",
                 family = "binomial")
    out <- append(out,mod)
}

我收到一个错误，说变量长度不同(在‘f’中找到)。我认为它没有将f识别为列名？我该如何解决这个问题呢？

Answer 1

作为将来的参考，一个带有reprex的答案使用了@Rorschach探测到的相同的解决方案：

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)
}