similar to: [handling] Missing [values in randomForest]

Hello everybody, this is my first request about R so I am sorry if I send it to a bad mail or if I am not very clear. So my problem is about the use of rfImpute from randomForest package. I am interested in imputations of missing values and I read that randomForest can make it. So i write the following code : set.seed(100); library(mlbench) library(randomForest) data(BreastCancer)

In trying to execute this line in R (Version 1.7.1 (2003-06-16), under windows XP pro), with the randomForest library (about two weeks old) loaded, the program crashed: bost4rf <- rfImpute(TargetDensity~.,data=bost4rf0) Specifically, an XP dialog box popped up, saying ?R for windows GUI front-end has encountered a problem and needs to close.? That was the dialog saying asking whether I

Does anyone know a reason why, in principle, a call to randomForest cannot accept a data frame with missing predictor values? If each individual tree is built using CART, then it seems like this should be possible. (I understand that one may impute missing values using rfImpute or some other method, but I would like to avoid doing that.) If this functionality were available, then when the trees

Dear all, Version 4.3-0 of the randomForest package is now available on CRAN (in source; binaries will follow in due course). There are some interface changes and a few new features, as well as bug fixes. For those who had used previous versions, the important things to note are: 1. there's a namespace now, and 2. some functions have been renamed. The list of changes since 4.0-7 (last

Dear all, Version 4.3-0 of the randomForest package is now available on CRAN (in source; binaries will follow in due course). There are some interface changes and a few new features, as well as bug fixes. For those who had used previous versions, the important things to note are: 1. there's a namespace now, and 2. some functions have been renamed. The list of changes since 4.0-7 (last

I have a question regarding NA in randomForest (in R). I have a dataset which include both numerical and non-numerical variables, and the data includes some NA. I tried to use na.roughfix but then i get an error message "na.roughfix only works for numeric or factor". I also tried rfImpute but this does not work either because I have some NA in my response variable. Does anyone have som

Dear R users, I've just released a new version of randomForest (available on CRAN now). This version contained quite a number of new features and bug fixes, compared to version prior to 4.0-x (and few more since 4.0-1). For those not familiar with randomForest, it's an ensemble classifier/regression tool. Please see http://www.math.usu.edu/~adele/forests/ for more detailed information,

Dear R users, I've just released a new version of randomForest (available on CRAN now). This version contained quite a number of new features and bug fixes, compared to version prior to 4.0-x (and few more since 4.0-1). For those not familiar with randomForest, it's an ensemble classifier/regression tool. Please see http://www.math.usu.edu/~adele/forests/ for more detailed information,

I am having trouble with the rfImpute function in the randomForest package. Here is a sample... clunk.roughfix<-na.roughfix(clunk) > > clunk.impute<-rfImpute(CONVERT~.,data=clunk) ntree OOB 1 2 300: 26.80% 3.83% 85.37% ntree OOB 1 2 300: 18.56% 5.74% 51.22% Error in randomForest.default(xf, y, ntree = ntree, ..., do.trace = ntree, : NA not

A few days ago I asked whether there were options other than na.action=na.fail for the R port of Breiman?s randomForest; the function?s help page did not say anything about other options. I have since discovered that a pdf document called ?The randomForest Package? and made available by Andy Liaw (who made the tool available in R---thank you) does discuss an option. It is an implementation of

Dear Administrator, I am using linux (suse 10.2). While attempting rfImpute, I am getting the following error message: > Members <- rfImpute(Status ~ ., data = Members) Error in .C("classRF", x = x, xdim = as.integer(c(p, n)), y = as.integer(y), : C symbol name "classRF" not in DLL for package "randomForest". I need the help to sort out above error.

I have a set of timestamp data that I have in a text file that I would like to import into R for analysis. The timestamps are formated as follows: DT_1,DT_2 [2006/08/10 21:12:14 ],[2006/08/10 21:54:00 ] [2006/08/10 20:42:00 ],[2006/08/10 22:48:00 ] [2006/08/10 20:58:00 ],[2006/08/10 21:39:00 ] [2006/08/04 12:15:24 ],[2006/08/04 12:20:00 ] [2006/08/04 12:02:00 ],[2006/08/04 14:20:00 ] I can get

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I tried rfImpute (randomForest) and as far as I understood should it replace NA`s using a proximity matrix: > set.seed(100000) > Subset5Imputed<-rfImpute(Sex~., data=Subset5) ntree OOB 1 2 300: 11.78% 12.36% 11.21% ntree OOB 1 2 300: 12.07% 12.64%

Dear All, I would like to use a randomForest algorithm on a dataset. The set is not particularly large/difficult to handle, but it has some missing values (both factors and numerical values). According to what I found https://stat.ethz.ch/pipermail/r-help/2005-September/078880.html https://stat.ethz.ch/pipermail/r-help/2007-January/123117.html the randomForest package has a problem with missing

Hi all, I am using the package "random forest" for random forest predictions. I like the package. However, I have fairly large data sets, and it can often take *hours* just to go through the "na.roughfix" call, which simply goes through and cleans up any NA values to either the median (numerical data) or the most frequent occurrence (factors). I am going to start

Dear all, Can anybody give me some hint on the following error msg I got with using randomForest? I have two-class classification problem. The data file "sample" is: ---------------------------------------------------------- udomain.edu udomain.hcs hpclass 1 1.0000 1 not 2 NA 2 not 3 NA 0.8 not 4 NA 0.2 hp 5 NA 0.9 hp ------------------------------------------------------------ The

> From: luk > > When I run randonForest with a 169453x5 matrix, I got the > following message. > > Error in matrix(0, n, n) : matrix: too many elements specified > > Can you please advise me how to solve this problem? > > Thanks, > > Lu 1. When asking new questions, please don't reply to other posts. 2. When asking questions like these, please

Hi all, We're using Rserve and RandomForest to do classification from within a Java program. The total is about 4 lines of R code: library('randomForest') x y future fit<-randomForest(x,y,no.action=na.roughfix,importance=T,proximity=T) p<-predict(fit, future) What is very frustrating is that we have tried this two different ways (both work in R): 1. Load x, y, and future

Dear R-users, While making a prediction using the randomForest function (package randomForest) I'm getting the following error message: "Error in predict.randomForest(model, newdata = CV) : No forest component in the object" Here's my complete code. For reproducing this task, please find my 2 data sets attached ( http://www.nabble.com/file/p17855119/data.rar data.rar ).

While trying to train randomForest with my dataset, I am ending up with the following error Error in randomForest.default(datatrain, classtrain) : length of response must be the same as predictors My data looks like: A,B,C,D,Class 1,2,1,2,cl1 1,2,1,2,cl1 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,1,2,cl2 3,2,12,3,cl2 3,2,1,2,cl2 Actual dataset has around 4000