search for: ncompete

...yval, the fitted value of the response at each node, *and splits, a two > column matrix of left and right split labels for each node. * But from looking at the object, for example fit1 <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis) fit1$frame var n wt dev yval complexity ncompete nsurrogate yval2.1 yval2.2 yval2.3 yval2.4 yval2.5 1 Start 81 81 17 1 0.17647059 2 1 1.0000000 64.0000000 17.0000000 0.7901235 0.2098765 2 Start 62 62 6 1 0.01960784 2 2 1.0000000 56.0000000 6.0000000 0.9032258 0.0967742 4 <lea...

Hi, Suppose i have generated an object using the following : fit <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis) And when i print fit, i get the following : n= 81 node), split, n, loss, yval, (yprob) * denotes terminal node 1) root 81 17 absent (0.7901235 0.2098765) 2) Start>=8.5 62 6 absent (0.9032258 0.0967742) 4) Start>=14.5 29 0 absent (1.0000000

Hello there. I have fitted a rpart model. > rpartModel <- rpart(y~., data=data.frame(y=y,x=x),method="class", ....) and can use rpart$where to find out the terminal nodes that each observations belongs. Now, I have a set of new data and used predict.rpart which seems to give only the predicted value with no information similar to rpart$where. May I know how

We are trying to make a decision tree using rpart and we are continually running into the following error: > fit_rpart=rpart(ENROLL_YN~MINORITY,method="class") > summary(fit_rpart) Call: rpart(formula = ENROLL_YN ~ MINORITY, method = "class") n= 5725 CP nsplit rel error 1 0 0 1 Error in yval[, 1] : incorrect number of dimensions ENROLL_YN is a