Hi all I have a question about correct usage of persp(). I have a simple neural net-based XOR example, as follows:
library(nnet) xor.data <- data.frame(cbind(expand.grid(c(0,1),c(0,1)), c(0,1,1,0))) names(xor.data) <- c("x","y","o") xor.nn <- nnet(o ~ x + y, data=xor.data, linout=FALSE, size=1) # Create an (x.y) surface and predict over all points d <- data.frame(expand.grid(seq(0,1,.1), seq(0,1,.1))) names(d) <- c("x","y") p <- predict(xor.nn, d) zmat <- as.matrix(cbind(d,p)) Now my z matrix consists of x and y points, and the corresponding prediction value for each (x,y) tuple. What would be the best way to plot these? I tried persp(), but it didnt like the z matrix. Is there an alternative plot function that I could use (I am presuming I need one of the 3d variants)? Thanks Rory [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.