Net_based {NAC} | R Documentation |
Network-based Regularized Spectral Clustering.
Description
Network-based Regularized Spectral Clustering is a spectral clustering with regularized Laplacian method, fully established in fully established in Impact of Regularization on Spectral Clustering of Joseph & Yu (2016).
Usage
Net_based(Adj, K, tau = NULL, itermax = 100, startn = 10)
Arguments
Adj |
An |
K |
A positive positive integer which is no larger than |
tau |
An optional tuning parameter to add |
itermax |
|
startn |
|
Value
estall |
A factor indicating nodes' labels. Items sharing the same label are in the same community. |
References
Joseph, A., & Yu, B. (2016). Impact of Regularization on Spectral Clustering.
The Annals of Statistics, 44(4), 1765-1791.
doi:10.1214/16-AOS1447
Examples
# Simulate the Network
n = 10; K = 2;
theta = 0.4 + (0.45-0.05)*(seq(1:n)/n)^2; Theta = diag(theta);
P = matrix(c(0.8, 0.2, 0.2, 0.8), byrow = TRUE, nrow = K)
set.seed(2022)
l = sample(1:K, n, replace=TRUE); # node labels
Pi = matrix(0, n, K) # label matrix
for (k in 1:K){
Pi[l == k, k] = 1
}
Omega = Theta %*% Pi %*% P %*% t(Pi) %*% Theta;
Adj = matrix(runif(n*n, 0, 1), nrow = n);
Adj = Omega - Adj;
Adj = 1*(Adj >= 0)
diag(Adj) = 0
Adj[lower.tri(Adj)] = t(Adj)[lower.tri(Adj)]
Net_based(Adj, 2)