Kohonen SOM in R: How to give weights for certain variables in the BMU finding process?

I'm using the Kohonen package (see also self-organising-maps-for-customer-segmentation-using-r) for Self Organizing Maps (SOM), and I would like to know how to give weights for certain variables in the "Best Matching Unit" (BMU) in the map—the most similar node—finding process. How can I do this for some specific columns?

In other words, I want to remove the effect of some components on the organization map by setting its weight to 0. Removing those variables from the data without preamble is not an option because I need to find the "properties" of those variables.

• I can't quite understand your question. Are you wanting to weight different variables differently in the training process, or in the prediction process? Have you considered the supersom? May 3, 2019 at 4:16