Hi, I am using the rpart package to build a classification tree. I did manage to build a tree with data on a previous project. However, when attampting to build a tree on a project I am working on, I seem to be getting the error shown below: > nhg3.rp <- rpart(profitresp ~., nhg3, method="class") > plot(nhg3.rp, branch=0.4, uniform=T); text(nhg3.rp, digits=3) Error in yval[, 1] : incorrect number of dimensions The distribution of my binary dependent variable is: > table(nhg$profitresp) 0 1 3703 4360 I am using 105 potential predictor variables. I am trying to come up with a decision rule to identify profitable responders from non-responders to a mailing. Some other details are: > summary(nhg3.rp) Call: rpart(formula = profitresp ~ ., data = nhg3, method = "class") n= 8063 CP nsplit rel error 1 0.009451796 0 1 Error in yval[, 1] : incorrect number of dimensions > print(nhg3.rp) n= 8063 node), split, n, loss, yval, (yprob) * denotes terminal node 1) root 8063 3703 1 (0.4592583 0.5407417) * > printcp(nhg3.rp) Classification tree: rpart(formula = profitresp ~ ., data = nhg3, method = "class") Variables actually used in tree construction: character(0) Root node error: 3703/8063 = 0.45926 n= 8063 CP nsplit rel error 1 0.0094518 0 1 Any help is appreciated. Thanks much, Jude Ryan
Liaw, Andy
2004-Jun-12 01:25 UTC
[R] Error when I try to build / plot a tree using rpart()
You didn't get a tree. The output of print() tells you that you only have the root node. You may need to adjust some of the parameters with rpart(..., control=rpart.control(...)). See ?rpart.control. HTH, Andy> From: Jude Ryan > > Hi, > > I am using the rpart package to build a classification tree. I did > manage to build a tree with data on a previous project. However, when > attampting to build a tree on a project I am working on, I seem to be > getting the error shown below: > > > nhg3.rp <- rpart(profitresp ~., nhg3, method="class") > > plot(nhg3.rp, branch=0.4, uniform=T); text(nhg3.rp, digits=3) > Error in yval[, 1] : incorrect number of dimensions > > The distribution of my binary dependent variable is: > > table(nhg$profitresp) > > 0 1 > 3703 4360 > > I am using 105 potential predictor variables. I am trying to come up > with a decision rule to identify profitable responders from > non-responders to a mailing. > > Some other details are: > > summary(nhg3.rp) > Call: > rpart(formula = profitresp ~ ., data = nhg3, method = "class") > n= 8063 > > CP nsplit rel error > 1 0.009451796 0 1 > Error in yval[, 1] : incorrect number of dimensions > > > print(nhg3.rp) > n= 8063 > > node), split, n, loss, yval, (yprob) > * denotes terminal node > > 1) root 8063 3703 1 (0.4592583 0.5407417) * > > > printcp(nhg3.rp) > > Classification tree: > rpart(formula = profitresp ~ ., data = nhg3, method = "class") > > Variables actually used in tree construction: > character(0) > > Root node error: 3703/8063 = 0.45926 > > n= 8063 > > CP nsplit rel error > 1 0.0094518 0 1 > > Any help is appreciated. > > Thanks much, > > Jude Ryan > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > >