similar to: does rpart has similar function as edit.tree?

Hi, all, I am wondering if it is possible to set parameters of 'rpart' and 'tree' such that they will produce the exact same tree? Thanks. Auston Wei Statistical Analyst Department of Biostatistics and Applied Mathematics The University of Texas MD Anderson Cancer Center Tel: 713-563-4281 Email: wwei@mdanderson.org [[alternative HTML version deleted]]

Hi, there, I am having trouble using 'lrm' function in package 'Design'. Basically, the ' . ' after ' ~ ' wouldn't work. Here are some sample codes: > temp <- data.frame(a=c(rep(0,3),rep(1,3)),b=rnorm(6),c=c('a','b','c','a','b','c')) > lrm(a~.,data=temp) Error in terms.formula(formula, specials =

Hi, List, I am using function 'cph' in package 'Design'. I have run into this error message but could not find documentation after looking for a long time. Could someone help me out? What kind of problem it is in my data set and how to fix it? Thanks a lot! Auston Error in fitter(X, Y, strata = Strata, offset = offset, weights = weights, :NA/NaN/Inf in foreign function

Hi, List, I used the following codes to generate ps plots but foo.ps contains nothing. Would someone please point out what is wrong with my codes? Thanks a million! postscript('foo.ps') par(mfrow=c(2,1)) par(mfg=c(1,1)) hist(rnorm(100),col='blue') par(mfrow=c(2,2)) par(mfg=c(2,1)) hist(rnorm(50),col='blue') par(mfg=c(2,2)) hist(rnorm(60),col='blue') dev.off()

All the documentation that I have on survival splitting is found in the technical report you mention. However, there is both a short form and a long form of this on our web site, did you get the larger one (52 pages)? I admit it is not a lot. There are no other split algorithms implimented for survival data. It would be possible to add your own. Attached is a slightly updated version of the

I am trying to create a classification tree using either tree or rpart functions but when it comes to plotting the results the formatting I get is different than what I see in all the tutorials (like http://www.youtube.com/watch?v=9XNhqO1bu0A or http://www.youtube.com/watch?v=m3mLNpeke0I&feature=related or http://www.statmethods.net/advstats/cart.html "tree for kyphosis"). I am

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, I have a problem with library (rpart) (and/or library(tree)). I use a data.frame with variables "pnV22" (observation: 1, 0 or yes, no) "JTemp" (mean temperature) "SNied" (summer rain) I used function "rpart" to build a model: library(rpart) attach(data.frame) result <- rpart(pnV22 ~ JTemp + SNied) I got the following tree: n=55518 (50

There have been various messages about packages tree and rpart whilst I have been travelling, and I have now prepared updates. tree ==== Tree is one of the oldest packages on CRAN (Feb 2000 apart from adding the maintainer field), and I had been hoping that it would fade away in favour of rpart. 1) sys.parent needed to be replaced by parent.frame in all but the most recent R (post 1.3.0).

Hi Everyone, I'm working on building some classification trees, and up to this point I've been using rpart. However, I recently discovered the tree package, and found that it had some useful functions (in particular deviance(), which I would really like to use for my project). I can't seem to find an equivalent function for rpart. I've considered using tree() in place of

Hi, I have a question regarding how to get some partial information from the output of rpart, which could be used as the first argument to predict. For example, in my code, I try to learn a stump tree (decision tree of depth 2):    "fit        <- rpart(y~bx, weights = w/mean(w), control = cntrl)     print(fit)     btest[1,]  <- predict(fit, newdata = data.frame(bx)) " I found

The "tree" package has a nice function partition.tree() for drawing the (1D or) 2D partition in the case of only (one or) two predictors {See the examples in help(partition.tree)}. {and so does S-plus (not in a separate package though)}. It seems to me that there's no function with similar functionality available for rpart. Am I mistaken? Has anyone worked on this? One possible

I'm making a few functions to generate latex files describing rpart objects that are then \input-ed into a larger document. So far, the functions I have generate paragraphs containing enumerations of the predictors in pruned trees and the number of formed groups. Its easy enough to recover these. For instance, R> print ( tree ) n= 878 node), split, n, loss, yval, (yprob) *

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

Dear R community, as stated in Breiman et.al. (1984) and De'Ath & Fabricius (2000) using sums of absolute deviations about the median as an impurity measure gives robust trees. I would like to use this method in rpart. Has somebody already tried this method in rpart? Is there maybe already a script available somewhere? I am aware of the possibility to define usersplits myself with

Hi Experts, I am new to R, using decision tree model for getting segmentation rules. A) Using behavioural data (attributes defining customer behaviour, ( example balances, number of accounts etc.) 1. Clustering: Cluster behavioural data to suitable number of clusters 2. Decision Tree: Using rpart classification tree for generating rules for segmentation using cluster number(cluster id) as target

Dear useRs: I try to plot an rpart object but cannot get a nice tree structure plot. I am using plot.rpart and text.rpart (please see below) but the branches that connect the nodes overlap the text in the ellipses and rectangles. Is there a way to get a clean nice tree plot (as in the Rpart Mayo report)? I work under Windows and use R2.11.1 with rpart version 3.1-46. Thank you. Tudor ...

Greetings, I am using rpart for classification with "class" method. The test data is the Indian diabetes data from package mlbench. I fitted a classification tree firstly using the original data, and then exchanged the order of Body mass and Plasma glucose which are the strongest/important variables in the growing phase. The second tree is a little different from the first one. The

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