dbscan (version 0.9-3)

frNN: Find the Fixed Radius Nearest Neighbors

Description

This function uses a kd-tree to find the fixed radius nearest neighbors (including distances) fast.

Usage

frNN(x, eps, sort = TRUE, search = "kdtree", bucketSize = 10,
  splitRule = "suggest", approx = 0)

Value

A list with the following components:dista matrix with distances.ida matrix with ids.epseps used.

Details

For details on the parameters see kNN.

References

David M. Mount and Sunil Arya (2010). ANN: A Library for Approximate Nearest Neighbor Searching, https://www.cs.umd.edu/~mount/ANN/.

See Also

kNN for k nearest neighbor search.

Examples

data(iris)

# Find fixed radius nearest neighbors for each point
nn <- frNN(iris[,-5], eps=.5)

# Number of neighbors
hist(sapply(nn$id, length),
  xlab = "k", main="Number of Neighbors",
  sub = paste("Neighborhood size eps =", nn$eps))

# Explore neighbors of point i = 10
i <- 10
nn$id[[i]]
nn$dist[[i]]

plot(iris[,-5], col = ifelse(1:nrow(iris) %in% nn$id[[i]], "red", "black"))

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