GenieClustering {FCPS}

Genie Clustering by Gini Index

Description

Outlier Resistant Hierarchical Clustering Algorithm of [Gagolewski/Bartoszuk, 2016].

Usage

GenieClustering(DataOrDistances, ClusterNo = 0,
DistanceMethod="euclidean", ColorTreshold = 0,...)

Arguments

DataOrDistances

[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. Alternatively, symmetric [1:n,1:n] distance matrix

ClusterNo

A number k which defines k different clusters to be build by the algorithm.

DistanceMethod

See parDist, for example 'euclidean','mahalanobis','manhatten' (cityblock),'fJaccard','binary', 'canberra', 'maximum'. Any unambiguous substring can be given.

ColorTreshold

Draws cutline w.r.t. dendogram y-axis (height), height of line as scalar should be given

...

furter argument to genie like:

thresholdGini Single numeric value in [0,1], threshold for the Gini index, 1 gives the standard single linkage algorithm

Details

Wrapper for Genie algorithm.

Value

List of

Cls

If, ClusterNo>0: [1:n] numerical vector with n numbers defining the classification as the main output of the clustering algorithm. It has k unique numbers representing the arbitrary labels of the clustering. Otherwise for ClusterNo=0: NULL

Dendrogram

Dendrogram of hierarchical clustering algorithm

Object

Ultrametric tree of hierarchical clustering algorithm

Author(s)

Michael Thrun

References

[Gagolewski/Bartoszuk, 2016] Gagolewski M., Bartoszuk M., Cena A., Genie: A new, fast, and outlier-resistant hierarchical clustering algorithm, Information Sciences, Vol. 363, pp. 8-23, 2016.

See Also

HierarchicalClustering

Examples

data('Hepta')
Clust=GenieClustering(Hepta$Data,ClusterNo=7)