similar to: two party questions: terminal stats and second dataset

Dear R.Users, using ctree() (from "party" library) on a data.frame, I want to append a column with the references for the groups/segments detected. While these nodes are easy readable in output, I need a vector for my obs. Hints? Cheers -- Daniele Medri

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

Dear R users, I am trying to apply the analysis processed in a paper, on the data I'm working with. The data is: 80 patients for which I have survival data (time - days, and event - binary), and microarray expression data for 200 genes (predictor continuous variables). My data matrix "data.test" has ncol: 202 and nrow: 80. What I want to do is: - run recursive partitioning on

Hello All, I am using library "party" and I have found a curious/strange behaviour when trying to save the output of a ctree in a file via jpeg/png command. If you use: ################ library(party) airq <- subset(airquality, !is.na(Ozone)) airct <- ctree(Ozone ~ ., data = airq) plot(airct, terminal_panel = node_boxplot, drop_terminal = FALSE) ############### you get 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

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,

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

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

Dear mailing list, I am using the cforest() method from the party package to train a randomForest with ten input parameters which sometimes contain "NA"s. The predicted variable is a binary decision. Building the tree works fine without warnings or error messages, but when using the predict() statement for validation, I run in an error: forest <- cforest(V31 ~ V1+V2+V3,

Hi All, i've got a problem using the ctree function of the party package. I've searched around a lot but couldn't manage it. I've got an ordered factor as response. As far as i know i have to use scores to be able to use this ordered factor. But if i do so i get a tree which predicts all observations as the first level of my ordered factor. In order to test if i did anything

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

Hallo list, I'm wondering if there is a way to extract the path to terminal nodes in a BinaryTree object, e.g. ctree, like the function path.rpart in package rpart. Thanks, Sven

Hi List, I am unsuccessfully trying to beautify barplot outputs from ctree. For example I would like to rotate x-axis lables and resize/change font/type. mtree <- ctree(ME ~ ., data = mammoexp) plot(mtree,terminal_panel=node_barplot(mtree,col="black",fill=NULL, beside=TRUE, ylines=NULL, widths=1,gap=NULL, reverse=FALSE,id=FALSE))

Hi there, I need to extract the variable names from all nodes (except the terminal nodes) from a ctree object, e.g. library(party) mammoct <- ctree(ME ~ ., data = mammoexp) plot(mammoct) how can I extract the varnames from node 1 (SYMPT) and node 3 (PB) from the fitted object "mammoct"? Many Thanks, Sven

Hi, I''m having a weird validation issue. Validation isn''t working for certain attributes and, for some reason, it''s also affecting things outside of validation. For campers on certain camp types, we require some information about their school. I tried to validate the information this way: validates_presence_of :school_type, :if => Proc.new { |c| !c.booking.nil?

I'm hoping that folks out there with expertise in working with the party package can help me out here. My team is trying to convert party tree output into a text file format that can be read by our image processing software. We are running into difficulties because the way the two different programs identify their nodes is different. R numbers it's nodes 1, 2, 3, 4, 5, 6 etc. down the

Dear useRs, Version 0.8-1 of the `party' package will appear on CRAN and its mirrors in due course. This version implements two new tools: o `mob', an object-oriented implementation of a recently suggested algorithm for model-based recursive partitioning (Zeileis, Hothorn, Hornik, 2005) has been added. It works out of the box for partitioning (generalized) linear

Hello. I have following data: doze g1 g2 g3 g4 etc... 1200 a d 1100 b e 1158 c f 1500 a e 1403 c f ... etc. Doze - numeric, levels(g1)=c('a','b','c'), levels(g2)=c('d','e','f'). This is the data of genetic analysis, where the factors are genes and the numerical is some numerical value. I want to build up a function, which will do a preliminary

The commit 607d432d referred a static int array defined in ctree.h, and a static inline function (btrfs_super_csum_size) using this array, the obvious problem is every c file using that function would have a local copy of that int array, multiple c files calling would result multiple copies of that array: $ nm fs/btrfs/btrfs.ko | grep btrfs_csum_sizes 0000010c r btrfs_csum_sizes 00000114 r