Current R instructions: please download this dll and this set of R commands. Then start R and use commands like the following (adjusting them for the proper locations of knnTree.dll and knnTree.R):
> dyn.load ("h:/temp/knnTree.dll") > source ("h:/temp/knnTree.R") > data (iris) > set.seed (3) > samp <- sample (nrow(iris), 75, replace=F) > knn.var (iris[samp, c(5, 1:4)], theyre.the.same=T) This knn classifier is based on 75 observations. It uses 2 out of 4 variables without scaling. Training rate is 0.01333 , achieved at k = 27. > iris.knn <- knn.var (iris[samp, c(5, 1:4)], theyre.the.same=T) > predict (iris.knn, iris[-samp, c(5, 1:4)], iris[samp, c(5, 1:4)]) $rate  0.08
Old instructions: don't do this. For R and unix, go to the CRAN home page and download the package. (Under "Software" choose "Package Sources" and choose "knnTree.") This seems to work fine. However the same code does not seem to work under Windows. For that you should download knnTree.zip, which includes the R/S-Plus functions and their documentation as well as the DLL containing the compiled code. Details on the functions are included in the readme file which you can also view here.
If you prefer you can download the source files (sorry, temporarily unavailable) in ZIP form and compile them for your platform.