SharedNearestNeighborClustering: SNN clustering

In FCPS: Fundamental Clustering Problems Suite

SNN clustering

Description

Shared Nearest Neighbor Clustering of [Ertoz et al., 2003].

Usage

SharedNearestNeighborClustering(Data,Knn,

Radius,minPts,PlotIt=FALSE,

UpperLimitRadius,...)

Arguments

Data	[1:n,1:d] matrix of dataset to be clustered. It consists of n cases of d-dimensional data points. Every case has d attributes, variables or features.
Knn	Number of neighbors to consider to calculate the shared nearest neighbors.
Radius	Eps [Ester et al., 1996, p. 227] neighborhood in the R-ball graph/unit disk graph), size of the epsilon neighborhood. If NULL, automatic estimation is done using insights of [Ultsch, 2005].
minPts	Number of minimum points in the eps region (for core points). In principle minimum number of points in the unit disk, if the unit disk is within the cluster (core) [Ester et al., 1996, p. 228]. if NULL, its 2.5 percent of points.
PlotIt	Default: FALSE, if TRUE plots the first three dimensions of the dataset with colored three-dimensional data points defined by the clustering stored in Cls
UpperLimitRadius	Limit for radius search, experimental
...	Further arguments to be set for the clustering algorithm, if not set, default arguments are used.

Details

..

Value

List of

Cls	[1:n] numerical vector defining the clustering; this classification is the main output of the algorithm. Points which cannot be assigned to a cluster will be reported as members of the noise cluster with 0.
Object	Object defined by clustering algorithm as the other output of this algorithm

Author(s)

Michael Thrun

References

[Ertoz et al., 2003] Levent Ertoz, Michael Steinbach, Vipin Kumar: Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data, SIAM International Conference on Data Mining, 47-59, 2003.

See Also

sNNclust

Examples

data('Hepta')
out=SharedNearestNeighborClustering(
Hepta$Data, Knn=7,Radius=NULL,minPts=NULL,PlotIt = FALSE)

FCPS documentation built on Oct. 19, 2023, 5:06 p.m.