The cluster assignment proceeds as with k-means. Each point is assigned to the cluster closest to it.
The means are estimated for each cluster as in k-means. JMP then uses these means to set up a weighted regression with each variable as the response in the regression, and the SOM grid coordinates as the regressors. The weighting function uses a kernel function that gives large weight to the cluster whose center is being estimated. Smaller weights are given to clusters farther away from the cluster in the SOM grid. The new cluster means are the predicted values from this regression.

Help created on 10/11/2018