calc.diffusionKernelp: Computing the Random Walk Kernel matrix of network

In netClass: netClass: An R Package for Network-Based Biomarker Discovery

Description

Computing the Random Walk Kernel matrix of network

Usage

calc.diffusionKernelp(L, is.adjacency = TRUE, p = 3, a = 2)

Arguments

L	an adjacency matrix that represents the underlying biological network.
is.adjacency	using adjacency of graph or not
p	#(p) random walk step(s) of random walk kernel
a	constant value of random walk kernel

Value

R	Return a Random Walk Kernel matrix of given network, L.

Author(s)

Yupeng Cun [e-mail]

References

Kondor, R. I., & Lafferty, J. (2002, July). Diffusion kernels on graphs and other discrete input spaces. In MACHINE LEARNING-INTERNATIONAL WORKSHOP THEN CONFERENCE- (pp. 315-322).

See Also

See Also as classify.stsvm

Examples

library(netClass)
data(ad.matrix) 
#dk= calc.diffusionKernelp(L=ad.matrix, is.adjacency=TRUE, p=2,a=1)

netClass documentation built on May 29, 2017, 7:18 p.m.