```
set.seed(665544)
n <- 600
x <- cbind(runif(10, 0, 10)+rnorm(n, sd=0.2), runif(10, 0, 10)+rnorm(n,
sd=0.2))
par(bg="grey40")
ds <- dbscan(x, 0.2)
# run with showplot=1 to see how dbscan works.
ds
plot(ds, x)
x2 <- matrix(0,nrow=4,ncol=2)
x2[1,] <- c(5,2)
x2[2,] <- c(8,3)
x2[3,] <- c(4,4)
x2[4,] <- c(9,9)
predict(ds, x, x2)
n <- 600
x <- cbind((1:3)+rnorm(n, sd=0.2), (1:3)+rnorm(n, sd=0.2))
# Not run, but results from my machine are 0.105 - 0.068 - 0.255:
# system.time(ds <- dbscan(x, 0.3, countmode=NULL, method="raw"))[3]
# system.time(dsb <- dbscan(x, 0.3, countmode=NULL, method="hybrid"))[3]
# system.time(dsc <- dbscan(dist(x), 0.3, countmode=NULL,
# method="dist"))[3]
```

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