similar to: tree.control

I have a problem with running the tree package (dec.8, 2001) for R. The problem is, it will only give me 5/6 terminal node and then stop, while using Splus's tree on the same data with the same specification give me hundreds of nodes. Here's a little more background info: R-1.4.1 Solaris 5.7 rpart (most recent version) tree (..) Splus 6.0 Solaris 5.7 tree

Hi. I'm using the tree package to fit one tree from a training set. I'm using the command: hm.tr <-tree(X1~.,teste2, mindev = 0, minsize = 2) and i get the error: Error in "row.names<-.data.frame"(*tmp*, value = fit$node[1:n]) : duplicate row.names are not allowed the frameset, has 180 columns and 16000 rows. The

Estimados compañeros hace unos días instale la versión última de R (3.4.1) en windows 10 y hoy me tiene loco el siguiente error cuando ejecuto predict para un árbol de clasificación-regresión. El problema da incluso con el ejemplo del comando predict library(tree) data(shuttle, package="MASS") shuttle.tr <- tree(use ~ ., shuttle, subset=1:253, mindev=1e-6,

Dear R community I have a question regarding the value of cost complexity parameter "k" used in "tree" package for pruning purpose. Any help in finding the optimum value of "k" is requested. Please give some suggestion in this regard. In the example below i used k=0 but i don't know why? But if i use k=NULL, then it will not plot the resultant tree.

Gracias Carlos miraré el fix y en su defecto intentaré mandar un mensaje al autor. De todas las maneras espero que alguien lo pruebe en windows 10 Saludos, Juan El 24/09/2017 a las 20:32, Carlos Ortega escribió: > Hola Juan Antonio, > > Acabo de instalar "tree" en Mac OSX y no aparece este error... > > > shuttle1 <- shuttle[254:256, ]  # 3 missing cases >

Dear All, We came across a problem when using the "tree" package to analyze our data set. First, in the "tree" function, if we use the default value "mindev=0.01", the resulting regression tree has a single node. So, we set "mindev=0", and obtain a tree with 931 terminal nodes. However, when we further use the "cv.tree" function to run a 10-fold

Dear R community Hope all of you are fine. I have a question regarding the an error message. Actually, I am trying to generate classification trees using "tree" package. It works well but for some datasets e.g., wine, yeast, boston housing etc. it gives an error message. Error in tree(V14 ~ ., data = training.data, method = c("recursive.partitioning"), : maximum

Hi, I have a dataframe, y, with 1000 rows and 266 columns. The first column of y is a 2 level factor response; columns 2:266 are each ordinal variables that can take on one of the values 1, 2, or 3. I'm trying to fit a model with the calls: (A) y.tree <- tree(pref~.,data=y,mindev=0,minsize=2) and (B) y.tree <- tree(pref~.,data=y,split='gini') pref is the name of the factor

I am using tree() in the library tree to learn regression trees. Once in a while I am getting the error "Tree is too big". From the same data set, but with randomized subsets I am learning several tree model and in the end of the day I would like to look at some of the properties across trees. My problem: I have for loop containing a call to tree(). However, since tree() returns an

Full_Name: Petr Savicky Version: 1.5.0 OS: SuSE 7.2 Submission from: (NULL) (147.231.6.1) The function tree() from the tree package crashes for certain input data. All the information needed to reproduce the error (data, script, expected error message) may be found at http://www.cs.cas.cz/~savicky/tree_error/tree_error.tgz Exactly the same error appeared at another computer running some RedHat

I am trying to use tree to partition a data set. The data set has 3924 observations. Partitioning seems to work for small subsets of the data, but when I use the entire data set, no partitioning occurs. The variables are: RESP respondent to a survey (0 = not a respondent, 1 = respondent) AGE_P Age (continuous) ORIGIN_I Hispanic Ethnicity (1 = Hispanic, 2 = non-Hispanic) RACRECI2 Race

> On Aug 20, 2015, at 9:46 AM, Steve King <steve at metrokings.com> wrote: > > On Wed, Aug 19, 2015 at 10:58 PM, Mehdi Amini <mehdi.amini at apple.com> wrote: >> >> Isn’t the problem the fact that the patch makes it harder for a target to >> get the generic code to reach its custom hook? >> Now the "cheap pow2 sdiv” is merged with the generic

Hi, On 08/07/2015 10:30 PM, Nick Lewycky wrote: [...] > Depends. What is the exact declaration of format_long? > > > In the input .ll file it is: > > ; Function Attrs: minsize optsize > define internal i16 @format_long(i16* %res.8.par, i16 %base.9.par, > i32 %x.10.par) #3 { > > which is later changed somewhere in opt to: > > ;

Dear R users, I have a question on the confusion matrix generated by function randomForest. I used the entire data set to generate the forest, for example: > print(iris.rf) Call: randomForest(formula = Species ~ ., data = iris, importance = TRUE, keep.forest = TRUE) confusion setosa versicolor virginica class.error setosa 50 0 0 0.00

Hi R-users, I am a new user to R language for statistical computing. I use a Windows 98 version. I downloaded tree add-on package to the R base system( I verified the local package submenu for the list of installed packages). But when I executed the following sample code given in the manual. I received an error "Couldn't find function tree" > data(iris) > ir.tr<-

On 08/07/2015 01:53 PM, Caldarale, Charles R wrote: >> From: llvm-dev [mailto:llvm-dev-bounces at lists.llvm.org] >> On Behalf Of Mikael Holmén via llvm-dev >> Subject: [llvm-dev] load instruction erroneously removed by GVN > >> But between the load and the alloca there is also >> call fastcc void @format_long(i16* %_tmp30, i16 10, i32 10), !dbg !22 >>

Hi all, I am running R1.5.0 under unix. I recently used the function 'predict.tree' to make predictions with a tree object and a dataframe of numeric items. The predict.tree internally, calls a function 'delete.response'. When I removed this function call from the source code of predict.tree, it ran 10 times faster without any differences in the result obtained. The

Hi, I am somewhat new to R so this question may be foolish, but is it possible to add decision trees into a list, array or vector in R? I am trying to build a collection (ensemble) of decision trees. Every time a new instance arrive I need to get the prediction of each decision tree. I have tried to add a decision tree into a variable but without luck. Is a special package needed perhaps? This

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]]

On Mon, Jan 14, 2013 at 10:48 PM, Evan Cheng <evan.cheng at apple.com> wrote: > > > Sent from my iPad > > On Jan 14, 2013, at 1:09 AM, Chandler Carruth <chandlerc at gmail.com> wrote: > > > This has been an idea floating around in my head for a while and after > several discussions with others it continues to hold up so I thought I > would mail it out.