```
# NOT RUN {
data(iris)
iris <- as.matrix(iris[,1:4])
## Find the 4-NN distance for each observation (see ?kNN
## for different search strategies)
kNNdist(iris, k=4)
## Get a matrix with distances to the 1st, 2nd, ..., 4th NN.
kNNdist(iris, k=4, all = TRUE)
## Produce a k-NN distance plot to determine a suitable eps for
## DBSCAN (the knee is around a distance of .5)
kNNdistplot(iris, k=4)
cl <- dbscan(iris, eps = .5, minPts = 4)
pairs(iris, col = cl$cluster+1L)
## Note: black are noise points
# }
```

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