similar to: bug in rpart?

Hi Prof. Williams, thanks for your suggestion. The updated code is below. It turns out it was a matter of displaying the second column in yval to get the number of N and subtracting it from the n column in the frame to get the number of Y remaining in a binary example. once this is added now the function returns the rules along with Y and N count affected by the resulting rule. I am ccing

Hi, I am new to R and need help with rpart. I am trying to create a classification tree using rpart. In order to plot the reults I use the plot function and the text function to label the plot of the tree dendrogram with text. The documentation of text.rpart says : "For the "class" method, label="yval" results in the factor levels being used, "yprob" results

Hello all, I'm was going through the help for ?rpart.object And noticed some inconsistencies, Some might be a mistake in the help file and some might be my misunderstanding. The help in the section: value -> frame (first paragraph), states that: > 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. *

Full_Name: Bill Wheeler Version: 2.0.1 OS: Windows 2000 Submission from: (NULL) (67.130.36.229) The program to reproduce the error is below. I am calling rpart with a user-defined split function for a binary response variable and one continuous independent variable. The split function works for some datasets but not others. The error is: Error in "$<-.data.frame"(`*tmp*`,

A few weeks back I posted that the subset feature of rpart was not working when predicting a categorical variable. I was able to figure out a simple solution to the problem that I hope can be included in future editions of rpart. I also include a fix for another related problem. The basic problem is that when predicting a categorical using a subset, the subset may not have all the categories

(Apparently, I posted this to the wrong place. I am hopefully posting this is the correct place now. If not, please advise.) A few weeks back I posted that the subset feature of rpart was not working when predicting a categorical variable. I was able to figure out a simple solution to the problem that I hope can be included in future editions of rpart. I also include a fix for another related

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

Hi, I am trying to use the rpart library with my own set of functions on a survival object. I get an immeadiate segmentation fault when i try calling rpart with my list of functions. I get the same problem with the logrank example from Therneau,s S-rpart library though their anova example works. Should I report this as a bug, as even if my functions are structured improperly, that should lead to

I tried using rpart, as below, and got this error message "rpart Error in yval[, 1] : incorrect number of dimensions". Thinking it might somehow be related to the large number of missing values, I tried using complete data, but with the same result. Does anyone know what may be going on, and how to fix it? I have traced two similar error messages in the Archive, but following the

Hello: I am using rpart and would like more background on how the splits are made and how to interpret results - also how to properly use text(.rpart). I have looked through Venables and Ripley and through the rpart help and still have some questions. If there is a source (say, Breiman et al) on decision trees that would clear this all up, please let me know. The questions below pertain to a

Hello All, Am I misreading the documentation? The text.rpart documentation says: "label a column name of x$frame; values of this will label the nodes. For the "class" method, label="yval" results in the factor levels being used, "yprob" results in the probability of the winning factor level being used, and ?specific yval level? results in the probability of

(I'm sending to r-bugs because rpart is one of the recommended packages and is always installed. I'm also sending it directly to Dr. Ripley, as the maintainer.) rpart working as a classifier does not work (produces no splits) when the class indicator has no instances of one of the factor levels, as long as the factor level is not the final level. I have at least a partial fix, which I

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

Hi R-helpers, I am using rpart package for decision tree using R.We are invoking R environment through JRI from our java application.Hence, the result of R command is returned in REXP and we use geterrMessage() to retrieve the error. When we execute the following command, cnr_model<-rpart(as.factor(Species)~Sepal Length+Sepal Width+Petal Length, method="class",

Dear all, I would like to model the relationship between y and x. y is binary variable, and x is a count variable which may be possion-distribution. I think it is better to divide x into intervals and change it to a factor before calling glm(y~x,data=dat,family=binomail). I try to use rpart. As y is binary, I use "class" method and get the following result. >

Dear r-list: I am using rpart to build a tree on a dataset. First I obtain a perhaps too large tree: > arbol.bsvg.02 <- rpart(formula, data = bsvg, subset=grp.entr, control=rpart.control(cp=0.001)) > arbol.bsvg.02 n= 100000 node), split, n, loss, yval, (yprob) * denotes terminal node 1) root 100000 6657 0 (0.93343000 0.06657000) 2) meses_antiguedad_svg>=10.5 73899 3658

I am trying to make a decision tree using rpart. The function runs very quickly considering the size of the data (1742, 163). When I call the summary command I get this: > summary(bookings.cart) Call: rpart(formula = totalRev ~ ., data = bookings, method = "class") n=1741 (1 observation deleted due to missingness) CP nsplit rel error 1 0 0 1 Error in yval[, 1] :

Hi All, I am fitting a tree to censored survival data using the rpart package and wanted to better understand the results. I am trying to interpret the output from the tree. I am interested in understanding what "yval" is for a survival tree. I see in the output of summary, the phrase "estimated rate". The estimated rate is 1 for the entire tree, and more of less for each

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

Hi, I am using rpart decision trees to analyze customer churn. I am finding that the decision trees created are not effective because they are not able to recognize factors that influence churn. I have created an example situation below. What do I need to do to for rpart to build a tree with the variable experience? My guess is that this would happen if rpart used the loss matrix while creating