Use this if you are using igraph from R
scg_eps {igraph} | R Documentation |
scg_eps
computes \Vert v_i-Pv_i\Vert
, where
v_i
is the i
th eigenvector in V
and P
is the
projector corresponding to the mtype
argument.
scg_eps(
V,
groups,
mtype = c("symmetric", "laplacian", "stochastic"),
p = NULL,
norm = c("row", "col")
)
V |
A numeric matrix of (eigen)vectors assumed normalized. The vectors
are to be stored column-wise in |
groups |
A vector of |
mtype |
The type of semi-projector used for the SCG. For now “symmetric”, “laplacian” and “stochastic” are available. |
p |
A probability vector of length |
norm |
Either “row” or “col”. If set to “row” the rows of the Laplacian matrix sum to zero and the rows of the stochastic matrix sum to one; otherwise it is the columns. |
scg_eps
returns with a numeric vector whose i
th
component is \Vert v_i-Pv_i\Vert
(see Details).
David Morton de Lachapelle, http://people.epfl.ch/david.morton.
D. Morton de Lachapelle, D. Gfeller, and P. De Los Rios, Shrinking Matrices while Preserving their Eigenpairs with Application to the Spectral Coarse Graining of Graphs. Submitted to SIAM Journal on Matrix Analysis and Applications, 2008. http://people.epfl.ch/david.morton
scg-method and scg
.
v <- rexp(20)
km <- kmeans(v,5)
sum(km$withinss)
scg_eps(cbind(v), km$cluster)^2