similar to: randomForest - NaN in %IncMSE

Hi everyone, I have another "Random Forest" package question: - my (presumably incorrect) understanding of the varImpPlot is that it should plot the "% increase in MSE" and "IncNodePurity" exactly as can be found from the "importance" section of the model results. - However, the plot does not, in fact, match the "importance"

Hello, I am running randomForest models on a number of species. I would like to be able to automate the printing of dependence plots for the most important variables in each model, but I am unable to figure out how to enter the variable names into my code. I had originally thought to extract them from the $importance matrix after sorting by metric (e.g. %IncMSE), but the importance matrix is n

I have a question about predictor importances in randomForest. Once I've run randomForest and got my object, I get their importances: rfresult$importance I also get the "standard errors" of the permutation-based importance measure: rfresult$importanceSD I have 2 questions: 1. Because I am dealing with regressions, I am getting an importance object (rfresult$importance) with two

Dear R-devel, Kurt had alerted me to the problem that the randomForest package that I maintain has been failing checks in R-devel. However, I just can't see why or where it's failing. I'd very much appreciate any pointer. The failure occur when running the example code in varImpPlot.Rd: > varImpPlot(mtcars.rf) Error in par(opar) : invalid value specified for graphical parameter

I am trying to use the package RandomForest performing regression. The variable importance estimates are given as: "%IncMSE" and "IncNodePurity" Can anyone explain me what these refer to and how they are calculated? I found a lot of information on variable importance measures for classification problems, but nothing on regression. Thanks a lot. Mareike

Hello, I am using the R randomForest package to classify variable stars. I have a training set of 1755 stars described by (too) many variables. Some of these variables are highly correlated. I believe that I understand how randomForest works and how the variable importance are evaluated (through variable permutations). Here are my questions. 1) variable importance error? Is there any ways

Full_Name: Daniel Normolle Version: 2.0.1 OS: Linux/Fedora Core 3 Submission from: (NULL) (141.214.17.5) varImpPlot in Random Forests 4.5-10 produces the error "incorrect number of subscripts on matrix" (and no plot) when applied to a randomForest object. This error did not occur with 4.5-4 or earlier versions.

Hi, I'm using package "caret" to rank predictors using random forest model and draw predictors importance plot. I used below commands: rf.fit<-randomForest(x,y,ntree=500,importance=TRUE) ## "x" is matrix whose columns are predictors, "y" is a binary resonse vector ## Then I got the ranked predictors by ranking

Dear R Helpers, I need help with a slightly unusual situation in which I am trying to select some columns from a data frame. I know how to use the subset statement with column names as in: x=as.data.frame(matrix(c(1,2,3, 1,2,3, 1,2,2, 1,2,2, 1,1,1),ncol=3,byrow=T)) all.cols<-colnames(x) to.keep<-all.cols[1:2] Kept<-subset(x,select=to.keep) Kept

I've run the function randomForest with importance=T. All my variables (predictors and the dependent variable) are numeric. rf<-randomForest(formula, data=mydata, importance=T, etc.) my results object "rf" contains predictor importances: rf$importance I am seeing two columns: %IncMSE IncNodePurity V1 -0.01683558 58.10910 V2 0.04000299 71.27579 V3 0.01974636

Hi I am trying to explore the use of random forests for regression to identify the important environmental/microclimate variables involved in predicting the abundance of a species in different habitats, there are approx 40 variable and between 200 and 500 data points depending on the dataset. I have successfully used the randomForest package to conduct the analysis and looked at the %IncMSE

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

Hi I am new to R so I apologize if this is trivial. I am trying to predict the resistance or susceptibility of my sequences to a certain drug with a randomForest function from a file with amino acids on each of the positions in the protein. I ran the following: > library(randomForest) > > path <- "C:\\..." > path2 <- "..." > name <-

Hi, I have been using some code for multivariate random forests. The output from this code is a list object with all the same values as from randomForest, but the model object is, of course, not of the class randomForest. So, I was hoping to modify the code for predict.randomForest to work for predicting the multivariate model to new data. This is my first attempt at modifying code from a

Dear R-help, This is about randomForest's handling of NA and NaNs in test set data. Currently, if the test set data contains an NA or NaN then predict.randomForest will skip that row in the output. I would like to change that behavior to outputting an NA. Can this be done with flags to randomForest? If not can some sort of wrapper be built to put the NAs back in? thanks, Clayton

How do I read/interpret the output of varImpPlot() for a randomForest object? Regards, Divya -------------------------------------------------------- [[alternative HTML version deleted]]

Hi, i try several possibilities adn looking in the archive, but didn't getting success to install j.lindsey's usefuel "library repeated" on my linux (suse9.0 with kernel 2.6.7,R.1.9.1) P.S. Windows, works fine Many thanks for help Christian chris at linux:/space/downs> R CMD INSTALL - l /usr/lib/R/library repeated WARNING: invalid package '-' WARNING:

> importance(rfor.pdp11_t25.comb1,type=1) %IncMSE v1 -0.28956401263 v2 1.92865561147 v3 -0.63443929130 v4 1.58949137047 v5 0.03190940065 I wasn't entirely confident with interpreting these results based on the documentation. Could you please interpret? [[alternative HTML version deleted]]

Dear R-users, I have a problem with randomForest{outlier}. After running the following code ( that produces a silly data set and builds a model with randomForest ): ####################### library(randomForest) set.seed(0) ## build data set X <- rbind( matrix( runif(n=400,min=-1,max=1), ncol = 10 ) , rep(1,times= 10 ) ) Y <- matrix( nrow = nrow(X), ncol = 1) for( i in (1:nrow(X))){