gtm_bi {gtm} | R Documentation |
The value is calculated from the average distance between the nearest neighbours in Y, the centres of the constrained Gaussian mixture generated in the target space from latent sample.
beta = gtm_bi(Y)
Y |
a matrix containing the positions of the centres of the Gaussian mixture induced in target space from the latent variable samples. |
beta
- an initial value for the inverse variance of the Gaussian mixture
T = matrix(3:61/20, ncol=1); T = cbind(T, T + 1.25 * sin(2*T)); # plot of sample data plot(T[,1], T[,2], col='red', pch=21, xlim=c(0, 3.5), ylim=c(0,3.5)) # setup and training X = gtm_pts(20) MU = gtm_pts(5) sigma = 1 FI = gtm_gbf(MU, sigma, X) W = gtm_ri(T, FI); Y = FI # plot of initialized data matplot(Y[,1], Y[,2], col='green', add=TRUE, type='p', pch=23) beta = gtm_bi(Y) symbols(x=Y[,1], y=Y[,2], circles=matrix(sqrt(1/beta) ,ncol=1,nrow=nrow(Y)), fg="green",add=TRUE, inches=FALSE);