library(dbscan)
## generating data -------------------------
set.seed(1839)
n <- 5000
x <- rbeta(n, .4, .4)
y <- rbinom(n, 1, x)
z <- ifelse(y == 1, 0, 1)
dat <- data.frame(x, y, z)

## selecting eps ---------------------------
kNNdistplot(dat, 9)
abline(h = .0045) # at the elbow

## clustering ------------------------------
# redundant column
set.seed(1839)
c1 <- dbscan(dat, .0045, 9)

# no redundant columns
set.seed(1839)
c2 <- dbscan(dat[, -3], .0045, 9)

## equivalent? -----------------------------
all.equal(c1$c, c2$c)