rw.kernel-methods | R Documentation |
Methods to compute the random walk kernel (Smola and Kondor, 2003)
## S4 method for signature 'matrix' rw.kernel(W, a = 2) ## S4 method for signature 'graph' rw.kernel(W, a = 2) ## S4 method for signature 'graph' p.step.rw.kernel(RW, p = 2) ## S4 method for signature 'matrix' p.step.rw.kernel(RW, p = 2)
W |
a square symmetric matrix with positive values or an object of the class graphAM or graphNEL of the package graph |
RW |
matrix. It must be a random walk kernel matrix |
a |
numeric. It is correlated to the probability of remaining at the same vertex. Larger a, larger the probability (def. 2) |
p |
integer. Number of steps (def: p=2) |
rw.kernel
methods computes the one step random walk kernel RW, i.e.:
RW = (a-1)I + D^{-\frac{1}{2}} * W * D^{-\frac{1}{2}}
where I is the identity matrix, W is the weighted adjacency matrix of an undirected graph, and D is a diagonal matrix with D_{ii} = ∑_j W_{ij}
p.step.rw.kernel
methods compute the p-step random walk kernel pRW, i.e.:
pRW = RW^p
rw.kernel
: A numeric square matrix representing a one-step random walk kernel matrix
p.step.rw.kernel
: A numeric square matrix representing a p-step random walk kernel matrix
signature(W = "graph")
rw.kernel
computes the random walk kernel starting from a graph of class graph
(hence including objects of class graphAM and graphNEL from the package graph)
signature(W = "matrix")
rw.kernel
computes the random walk kernel starting from a weighted adjacency matrix representing the graph
signature(RW = "graph")
p.step.rw.kernel
computes the a p-step random walk kernel starting from a graph of class graph
(hence including objects of class graphAM and graphNEL from the package graph)
signature(RW = "matrix")
p.step.rw.kernel
computes the p-step random walk kernel starting from a one-step random walk kernel matrix
# Random walk kernel computation using Functional Interaction network data library(bionetdata); data(FIN.data); W <- as.matrix(FIN.data); K <- rw.kernel(W); # this a 2-step random walk kernel K2 <- p.step.rw.kernel(K, p=2);
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