similar to: R, ctree and categorical variables

I have run the ctree function, and my dependent variable is broken into 3 categories: low cost, moderate cost and high cost. When i plot the results (eg. using plot(test.ct)), the plot shows, at the very bottom of each node, the probability of falling into each cost category. When i print the actual results (eg. using print(test.ct)), i get all of the backup

Hello. I have used the "party" package to generate a regression tree as follows: >origdata<-read.csv("origdata.csv") >ctrl<-ctree_control(mincriterion=0.99,maxdepth=10,minbucket=10) >test.ct<-ctree(Y~X1+X2+X3,data=origdata,control=ctrl) The above works fine. Orig data was my training data. I now have a test data file (testdata), and

Hello, When evaluating different learning methods for a categorization problem with the (really useful!) caret package, I'm getting confusing results from the Kappa computation. The data is about 20,000 rows and a few dozen columns, and the categories are quite asymmetrical, 4.1% in one category and 95.9% in the other. When I train a ctree model as: model <- train(dat.dts,

After ctree builds a tree, how would I determine the direction missing values follow by examining the BinaryTree-class object? For instance in the example below Bare.nuclei has 16 missing values and is used for the first split, but the missing values are not listed in either set of factors. (I have the same question for missing values among numeric [non-factor] values, but I assume the answer

Hello, This is a re-submittal of question I submitted last week, but haven't rec'd any responses. I need to extract the probabilities used to construct the barplots displayed as part of the graph produced by plot("ctree"). For example, library(party) iris.ct <- ctree(Species ~ . , data = iris) plot(iris.ct) Instead of a simple example with only 4 terminal nodes, my

I tried to use ctree but am not sure about the meaning of the plot. My.data.ct<-ctree(Resp~., data=My.data) plot(My.data.ct) My data.frame contains 88 explanatory variables (continous,ordered/unordered multistate,count data) and one response with two groups. In the plot are only two variables shown (2 internal nodes) and 3 final nodes. Does it mean that only these two variables show a

Hi, I have a problem with ctree of party package. I have data on distribution of more than one species (about 50 species) and I would like identify the relation of this multivariate object (species distribution) with a number of explanatory variables. rs is the name of my dataframe containing the species (columns from 2 to 51) and the explanatory variables (columns 52 and 53). Rows are my

Like earth can be trained simultaneously for degree and nprune, is there a way to train ctree simultaneously for mincriterion and maxdepth? Also, I notice there are separate methods ctree and ctree2, and if both options are attempted to tune with one method, the summary averages the option it doesn't support. The full log is attached, and notice these lines below for

I'm trying to understand how to set graphical parameters for trees created with the party package.  For example take the following code:   library(party)     data(airquality)     airq <- subset(airquality, !is.na(Ozone))     airct <- ctree(Ozone ~ ., data = airq,                    controls = ctree_control(maxsurrogate = 3))     plot(airct)   My problem is, I've got a ctree that has

When plotting Binary Trees (ctree) from the party package, is there a way to adjust the font sizes of the leaves? require(party) irisct <- ctree(Species ~ ., data = iris) plot(irisct) I want to adjust the font sizes for "Node 2", "Node 5", etc. I'd also like to be able to adjust the font sizes for the x-axis and y-axis labels of the histograms. Thanks,

Hello Josef, FYI build failure occured in fs/btrfs/ctree.h. CC fs/btrfs/super.o In file included from fs/btrfs/delayed-inode.h:30:0, from fs/btrfs/super.c:45: fs/btrfs/ctree.h:3235:1: error: expected identifier or ‘(’ before ‘<<’ token make[3]: *** [fs/btrfs/super.o] Error 1 make[2]: *** [fs/btrfs] Error 2 make[1]: *** [fs] Error 2 make[1]: Leaving directory ` make:

Hello, I've been using ctree and have developed a 55 node - 28 terminal solution. As can be imagined, the plot is difficult to travel down each of the major branches. I've read the help files for ctree I saw where terminal nodes can be color coded. plot(airct, type = "simple") > plot(airct, terminal_panel = node_boxplot(airct, col = "blue", + fill = hsv(2/3,

Dear all, I was intrigued by the ctree command and wanted to check it out. I first ran the demo with example(ctree) and did get the survival graphs in the end. Upon doing this with my own data and yielding a "Invalid operation on a survival time" I tried to rerun example(ctree) and now I also get "Invalid operation on a survival time" after the example runs plot(GBSG2ct)...

Hi All, I'm using the party package to grow conditional inference trees for survival analysis. When I used party version party_0.9-9991 everything worked well, but when I update to party_1.0-2 (due to using 64bit R), I get an error. For simplicity I will show the error I get for the example in the party documentation: ### survival analysis if (require("ipred")) {

Hello, I need to classify (i.e., export a vector with terminal node id's) new cases using a ctree (party package) model based on different cases (learning sample). I tried the where command with the following syntax: > where(tree, newdata=data2) expecting to get terminal nodes of data2 cases based on rules of tree model (data1 as learning sample). However it returned the following error

Hello, I noticed a double definition of BTRFS_CSUM_TYPE_CRC32 in ctree.h and attach a patch that removes it. Best regards, Dirk

Hi, I am trying to get the terminal nodes of a plot of a ctree object to look nice. Using the iris data I have: library(party) mtree <- ctree(Species ~ ., data=iris) plot(mtree,terminal_panel=node_barplot(mtree)) The terminal nodes don't display the species names because the names are displayed horizontally. ?I would like to reduce the size of the labels and make the terminal nodes

Hello, My question is related to ctree() function from the library 'party'. Is there a way to force ctree() to use a specific variable in the first split? I am asking because the first split contains two variables with very similar scores, and choosing the alternative variable would induce a tree somewhat easier to interpret. Thanks, Sal

Hi, I am new to R and am using the ctree() function to do customer segmentation. I am using the following code to generate the tree: treedata$Response<-factor(treedata$Conversion) fit<-ctree(Response ~ .,controls=ctree_control(mincriterion=0.99,maxdepth=4),data=treedata) plot(fit) print(fit) The variable "Response" above equals 1 if the customer responded to an offering and

Hello! I am not familiar to deal with S4 objects in R, so this question can be stupid, but I hope I can get an answer. :P I'm trying to extract what are the response and explanatory variables from a Binary Tree and Random Forest. I could already extract the response variable from a Binary Tree using the response method specified on documentation. But Random Forest didn't had a similar