similar to: rpart/tree issue

Hi, when I have made a decision tree with rpart, is it possible to "apply" this tree to a new set of data in order to find out the distribution of observations? Ideally I would like to plot my original tree, with the counts (at each node) of the new data. Reagards, Jay

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

I was glad to see the new rpart.plot package by Stephen Milborrow. I was however a bit concerned that Stephen distributed a dataset I created, and renamed the dataset (from titanic3 to ptitanic) in the process [with some justification, as some variables were omitted]. Fortunately Stephen included the script he used to download the dataset from our web site, and gave full credit to us. What

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 ...

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 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, 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

Dear R-users I am using RPART package to get regression trees. However having trouble getting the text function to put the full splitting rule number on the plot, instead to puts it in scientific notation. When a covariate has 1e4 or greater number of digits then the splitting rule number displayed on the plot is in scientific notation. But print.rpart displays the splitting rules in full.

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

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

In the help for rpart it says, "This differs from the tree function mainly in its handling of surrogate variables." And it says that an rpart object is a superset of a tree object. Both cite Brieman et al. 1984. Both call external code which looks like martian poetry to me. I've seen posts in the archives where BDR, and other knowledgeable folks, have said that rpart() is to be

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

Hi, I have one question: Does the rpart tree construction have a depth limith for the tree? Thanks a lot Hugo -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject

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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

Hello, I am using the RPART library to find patterns in HIV mutations regarding drug-resistancy. My data consists of aminoacid at certain locations and two classes resistant and susceptible. The classification and pruning work fine with Rpart. however there is a problem with displaying the data as a tree in the display window. in the display window the data contain only levels at the splits

Hi all, I am using the rpart library to construct wildlife distribution models. As many of the sites that we have sampled have been sampled over many years, we would like to evaluate binomial responses (number of years that the species was present vs. number of years it was absent at a particular site). Does anybody know if the rpart function can evaluate binomial responses? If not, are there

Hi I was wondering if someone could help me with an rpart problem. I can see that cross-validation is the default for tree selection in rpart -- has a bootstrap method been implemented anywhere? I think this is a different thing to 'bagging' or 'boosting' -- I still want 'one' tree at the end, I just would like it chosen using a bootstrap method. Any ideas??? Thanks

partition.tree plots in 2d the partition of a classification tree produced by the function tree (assuming the data frame from which it was computed has two continuous predictors). I get an error when I feed a tree produced by rpart to partition.tree (since trees produced by rpart are superclasses of those produced by tree). Is there an equivalent of partition.tree for objects of class rpart?

Hi - I'm trying to append simple density histograms of a continuous variable to the leaves of an rpart tree. The splits in the tree are all levels of a factor and I'm hoping to make the histograms out of the subsets of the dataframe corresponding to the splits and for them to be attached to the appropriate leaf of the final tree. Any help would be much appreciated, thanks, Jon Zelner