ModelBasedClustering: Model Based Clustering

In Mthrun/FCPS: Fundamental Clustering Problems Suite

Model Based Clustering

Description

Calls Model based clustering of [Fraley/Raftery, 2006] which models a Mixture Of Gaussians (MoG).

Usage

ModelBasedClustering(Data,ClusterNo=2,PlotIt=FALSE,...)

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.
ClusterNo	A number k which defines k different clusters to be built by the algorithm.
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
...	Further arguments to be set for the clustering algorithm, if not set, default arguments are used.

Details

see [Thrun, 2017, p. 23] or [Fraley/Raftery, 2002] and [Fraley/Raftery, 2006].

Value

List of

Cls	[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.
Object	Object defined by clustering algorithm as the other output of this algorithm

Note

MoGclustering used in [Thrun, 2017] was renamed to ModelBasedClustering in this package.

Author(s)

Michael Thrun

References

[Thrun, 2017] Thrun, M. C.:A System for Projection Based Clustering through Self-Organization and Swarm Intelligence, (Doctoral dissertation), Philipps-Universitaet Marburg, Marburg, 2017.

[Fraley/Raftery, 2002] Fraley, C., and Raftery, A. E.: Model-based clustering, discriminant analysis, and density estimation, Journal of the American Statistical Association, Vol. 97(458), pp. 611-631. 2002.

[Fraley/Raftery, 2006] Fraley, C., and Raftery, A. E.MCLUST version 3: an R package for normal mixture modeling and model-based clustering,DTIC Document, 2006.

See Also

MoGclustering

Examples

data('Hepta')
out=ModelBasedClustering(Hepta$Data,PlotIt=FALSE)

Mthrun/FCPS documentation built on June 28, 2023, 9:29 a.m.