search for: aa_ss

I make classification tree like this code p.t2.90 <- rpart(y~aa_three+bas+bcu+aa_ss, data=training,method="class",control=rpart.control(cp=0.0001)) Here I want to set weight for 4 predictors(aa_three,bas,bcu,aa_ss). I know that there is a weight set-up in rpart. Can this set-up satisfy my need? If so, could someone give me an example? Thanks, Aimin Yan

...and real observation. I run my code(see following) several time, but I get different correlation coefficient each time. Anyone know why? In addition, How to calculate prediction accuracy for prediction of continuous variable? Aimin thanks, > m.nn.omega <- nnet(omega~aa_three+bas+bcu+aa_ss, data=training, size=2, linout=TRUE) # weights: 57 initial value 89153525.582093 iter 10 value 15036439.951888 iter 20 value 15010796.121891 iter 30 value 15000761.804392 iter 40 value 14955839.294531 iter 50 value 14934746.564215 iter 60 value 14933978.758615 iter 70 value 14555668.38100...