spectralEmbeddingNg {RclusTool} | R Documentation |
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")
[Package RclusTool version 0.91.6 Index]