# NN

From dbscan v1.1-1
by Michael Hahsler

##### Nearest Neighbors Auxiliary Functions

- Keywords
- model

##### Usage

```
adjacencylist(x, ...)
# S3 method for NN
plot(x, data, main = NULL, ...)
```

##### Arguments

- x
a nearest neighbor object (of class kNN or frNN).

- ...
further arguments are currently ignored.

- data
data with the coordinates for plotting.

- main
main title for the plot.

##### Value

`adjacencylist`

returns
a list with one element for each original data point. Each element contains
the row ids of the nearest neighbors. The adjacency list can be used to create
for example a graph object.

##### See Also

##### Examples

```
# NOT RUN {
data(iris)
x <- iris[, -5]
# finding kNN directly in data (using a kd-tree)
nn <- kNN(x, k=5)
nn
# plot the kNN where NN are shown as line conecting points.
plot(nn, x)
# show the first few elements of the adjacency list
head(adjacencylist(nn))
# create a graph and find connected components
library("igraph")
g <- graph_from_adj_list(adjacencylist(nn))
comp <- components(g)
plot(x, col = comp$membership)
# detect clusters (communities) with the label propagation algorithm
cl <- membership(cluster_label_prop(g))
plot(x, col = cl)
# }
```

*Documentation reproduced from package dbscan, version 1.1-1, License: GPL (>= 2)*

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