gtm_pmn {gtm}R Documentation

Calculates the posterior mean projection of data into the latent space

Description

The posterior mean projection of a point from the target space, t, is the mean of the corresponding posterior distribution induced in the latent space.

Usage

means = gtm_pmn(T, X, FI, W, b)

Arguments

T data points representing the distribution in the target space. N-by-D
X data points forming a latent variable sample of the distribution in the latent space. K-by-L
FI activations of the basis functions when fed X; K-by-(M+1)
W a matrix of trained weights
b the trained value for beta

Value

means - the posterior means in latent space. N-by-L

See Also

gtm_ppd1,gtm_ppd2 gtm_pmd

Examples

   lv = gtm_demo()
   gtm_pmn(lv$T, lv$X, lv$FI, lv$W, lv$beta)
 


[Package gtm version 1.0 Index]