Round numbers at a threshold value in R

I'm trying to do logical regression and I got to the point where I have the probability for each observation. Now I would like to classify the probabilities to either 0 or 1 given a threshold value

For example, if I have two numbers 0.65 and 0.87 and my threshold is 0.7, I'd like to round 0.65 to 0 and 0.87 to 1.

To achieve this, I've tried the following code which I think is too much for such a simple task, and I'd like to know if there's any function dedicated to perform this.

library(tidyverse)

# create a table of probabilities and predictions (0 or 1)
df <- tibble(
  prob = runif(20),
  pred = round(prob) # threshold = 0.5
)

# threshold function for length = 1
threshold_1 <- function(p,t) {
  if (p > t) 1 else 0
}

# threshold function for length = p
threshold_p <- function(ps, t) {
  map2_dbl(ps, t, threshold_1)
}

# below works.
df %>% mutate(
  pred = threshold_p(df$prob, 0.7)
)

I've also tried this

# threshold = 0.7
df %>%
  mutate(
  pred = round(prob - 0.2) # threshold = 0.7
)

Above works quite nicely as no probability will be exactly 0 or 1 (as long as we're dealing with distribution functions), so even if I +/- 0.5 to the numbers (to change the threshold value), they will never round to -1 or 2. But it's just that it's not very elegant.

I'd like to know if there is any function that does this in a much simpler way?

---

听起来像ifelse可以做你想要的东西？

library(dplyr)
df %>% 
  mutate(pred = ifelse(prob < 0.7, 0, 1))

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