# Decision boundaries from coefficients of linear discriminants?

I have a data set with four variables and 3000+ observations on which I performed an LDA. I was wondering how I can use the scaled coefficients of linear discriminants (output of R shown below as example) to draw decision boundaries in the original variable space?

          LD1      LD2     LD3
[1,]  49.5077  12.3211 20.8351
[2,]  11.3597   9.5139  8.6570
[3,]  39.9696   2.3232  2.8996
[4,] -18.4602 -43.5083  1.1121

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