computeGaussianSimilarityZP {RclusTool} | R Documentation |
Gaussian similarity
Description
Compute a similarity matrix thanks a Gaussian kernel for which the parameters are self-tuned (according to Zelnik-Manor and Perona, 2004).
Usage
computeGaussianSimilarityZP(dat, k = 7)
Arguments
dat |
numeric matrix of data (point by line). |
k |
number of neighbour for the computation of local sigma (smooth parameter of Gaussian kernel). |
Details
computeGaussianSimilarityZP returns a similarity matrix computed thanks a Gaussian kernel for which the parameters are self-tuned (according to Zelnik-Manor and Perona, 2004)
Value
sim similarity matrix.
References
L. Zelnik-Manor, P. Perona, Self tuning spectral clustering, Adv. Neural Inf. Process. Systems (2004), pp. 1601-1608.
See Also
Examples
require(grDevices)
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 <- computeGaussianSimilarityZP(dat, 10)
pal <- colorRampPalette(c("blue", "red"))
image(sim, col = pal(10))
[Package RclusTool version 0.91.6 Index]