search for: aa_three

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 Ya...

...predicted value 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...