syntheticGaussian1: Synthetic Gaussian Cluster Data 1

In nsdumont/jDirichletMixtureModels: Dirichlet Mixture Models for Clustering using Julia backend

Description

Synthetic 2-d data with N=5000 vectors and k=15 Gaussian clusters with different degree of cluster overlapping

Usage

data(syntheticGaussian1, package = "jDirichletMixtureModels")

Format

An object of class matrix with 5000 rows and 2 columns.

Source

Clustering basic benchmark

References

P. Fr<c3><a4>nti and O. Virmajoki, "Iterative shrinking method for clustering problems", Pattern Recognition, 39 (5), 761-765, May 2006.

Examples

## Not run: 
Xdata <- data(syntheticGaussian1, package = "jDirichletMixtureModels")
states <- dmm.cluster(model, Xdata)
dmm.plot(states[[1]]$labeledData)

## End(Not run)

nsdumont/jDirichletMixtureModels documentation built on May 23, 2019, 2:51 p.m.