kNNdist

0th

Percentile

Fast caclulation of the k-nearest neighbor distances in a matrix of points. The plot can be used to help find a suitable value for the eps neighborhood for DBSCAN. Look for the knee in the plot.

Keywords
model, plot
Usage
kNNdist(x, k, ...)
kNNdistplot(x, k = 4, ...)
Arguments
x
the data set as a matrix or a dist object.
k
number of nearest neighbors used (use minPoints).
...
further arguments are passed on to kNN.
Details

See kNN for a discusion of the kd-tree related parameters.

Value

kNNdist returns a numeric vector with the distance to its k nearest neighbor.

See Also

kNN.

Aliases
  • kNNdist
  • kNNdistplot
Examples
data(iris)
iris <- as.matrix(iris[,1:4])

kNNdist(iris, k=4, search="kd")
kNNdistplot(iris, k=4)
## the knee is around a distance of .5

cl <- dbscan(iris, eps = .5, minPts = 4)
pairs(iris, col = cl$cluster+1L)
## Note: black are noise points
Documentation reproduced from package dbscan, version 1.1-1, License:

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