graphkernels (version 1.6.1)

CalculateExponentialRandomWalkKernel: Exponential random walk kernel

Description

This function calculates a kernel matrix of the exponential random walk kernel \(K_{ER}\).

Usage

CalculateExponentialRandomWalkKernel(G, par)

Arguments

G

a list of igraph graphs

par

a coefficient \(\beta\), with which the weight \(\lambda_k\) for each step \(k\) is given as \(\lambda_k = \beta^k / k!\)

Value

a kernel matrix of the exponential random walk kernel \(K_{ER}\)

References

Gartner, T., Flach, P., Wrobel, S.: On graph kernels: Hardness results and efficient alternatives, Learning Theory and Kernel Machines (LNCS 2777), 129-143 (2003) https://link.springer.com/chapter/10.1007/978-3-540-45167-9_11.

Examples

# NOT RUN {
data(mutag)
K <- CalculateExponentialRandomWalkKernel(mutag[1:5], .1)
# }