# Example code for fitting the neural network.

# This command tells S-Plus where to find the neural net library.
# For example if you placed the nnet library in the C:/public folder
# then you could use the form
# library(nnet, first=T, lib.loc="C:/public")

library(nnet, first=T)

# Now attach the uva.nomiss dataframe
attach(uva.nomiss)


# Here is an example of how to use Nick's command
# The command name is testnnet
# The inputs go into the cbind function, 
# (cbind builds them into a matrix) 
# The output is as.factor(uva.nomiss$Newbie), which tells S-Plus
# to treat Newbie as a categorical variable.
# So to explore various architectures you can try and add or delete
# variables in the cbind list, OR increase/decrease the size variable
# which controls the number of units in the hidden layer.

 
testnnet(
         cbind(uva.nomiss$Age/80,
               uva.nomiss$Income,
               uva.nomiss$Gender,
               uva.nomiss$Marital.Status),
         as.factor(uva.nomiss$Newbie),
         size=12,
         skip=T,
         decay=.0005,
         entropy=T)