get.best.eigenvectors: get best eigenvectors

In clusterpath: Fast agglomerative convex clustering, non-Rcpp implementation

Description

this implements the protocol in Ng Jordan 2001 NIPS for 2 clusters. weights are calculated for a range of gamma values. Kmeans is fit to the top 2 eigenvectors in each case, and we pick the eigenvectors the best reconstruction error

Usage

get.best.eigenvectors(S, K, evec.transform)

Arguments

S
K
evec.transform

Author(s)

Toby Dylan Hocking

Examples

set.seed(1)
sim <- gendata(N=20,D=2,K=2,SD=0.1)
pts <- data.frame(sim$mat,class=sim$class)
xyplot(X1~X2,pts,groups=class,aspect="iso")+
  layer_(ltext(x,y,1:length(x)))

best <- get.best.eigenvectors(sim$mat,2,e.usual.k(2))
vecs <- data.frame(as.matrix(best),class=sim$class)
xyplot(X1~X2,vecs,groups=class,aspect="iso")

best <- get.best.eigenvectors(sim$mat,2,e.exponential)
vecs <- data.frame(as.matrix(best),class=sim$class)
xyplot(X1~X2,vecs,groups=class,aspect="iso")

clusterpath documentation built on June 30, 2020, 3:02 a.m.