Hi, I was trying to use the nnet library and am not sure of whats going on. I am calling the nnet function as:
n <- nnet(x,y,size=3,subset=sets[[1]], maxit=200) Where x is a 272x4 matrix of observations (examples) and y is a 272x1 matrix of target values. However when I look at nnet$residuals they are off by two orders of magnitude (compared to the output from neural network code that I already have). Looking at nnet$fitted.values shows all the values to be 1 (whereas my target values range from 0 to 150). Am I making an obvious mistake in the way I'm calling the function? Is the fact that n$fitted.values is all 1's indicating that the NN is doing a classification? If so how can I make it do quantitation? The man page mentions that if the response is a factor then it defaults to quantitation. However my y matrix just contain numbers - so it should'nt be doing classification. Any pointers would be appreciated. Thanks, ------------------------------------------------------------------- Rajarshi Guha <[EMAIL PROTECTED]> <http://jijo.cjb.net> GPG Fingerprint: 0CCA 8EE2 2EEB 25E2 AB04 06F7 1BB9 E634 9B87 56EE ------------------------------------------------------------------- Psychology is merely producing habits out of rats. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
