spectralEmbeddingNg: Spectral embedding

In RclusTool: Graphical Toolbox for Clustering and Classification of Data Frames

Spectral embedding

Description

Build a spectral space from a similarity matrix (according to Ng et al., 2002).

Usage

spectralEmbeddingNg(sim, K)

Arguments

sim	similarity matrix.
K	number of clusters.

Details

spectralEmbeddingNg returns a spectral space built from a similarity matrix (according to Ng et al., 2002)

Value

The function returns a list containing:

x	matrix containing, in columns, the eigenvectors of the similarity matrix.
eigen.val	vector containing the eigenvalues of the similarity matrix.

References

A. Ng, M. Jordan, Y. Weiss, On spectral clustering: Analysis and an algorithm, Neural Inf. Process. Systems NIPS14 (2002), pp. 849-856.

Examples

dat <- rbind(matrix(rnorm(100, mean = 0, sd = 0.3), ncol = 2), 
           matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2), 
           matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2))

sim <- computeGaussianSimilarity(dat, 1)
res <- spectralEmbeddingNg(sim, K=3)

plot(res$x[,2], res$x[,3], type = "p", xlab = "2nd eigenvector", ylab = "3rd eigenvector")

RclusTool documentation built on Aug. 29, 2022, 9:07 a.m.