search for: varimpplot

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" section of the random forest model....

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.

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 "xaxp" Execution halted However, I do not have "par(opar)" or set xaxp anywhere in any of the .Rd or .R files in the package. In varImpPlot(), I used the construct: if (nm...

...s: 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 "rf1$importance[,"MeanDecreaseAccuracy"]" ## Then draw the importance plot varImpPlot(rf.fit) As you can see, all the functions I used are directly from the package "randomForest", instead of from "caret". so I'm wondering if the package "caret" has some functions who can do the above ranking and ploting. In fact, I tried functions "train&quo...

I'm calculating nodes using Random Forest in R but i only get nodes for a fraction of the compounds i want to calculate, the rest is ommited and is not printed in the output file, (i'm working with 3012 compounds). What can i do to have nodes printed for all the compounds. Thanks Gon?alo

Hi I am having a problem using varImpPlot in randomForest. I get the error message "Error in plot.window(xlim = xlim, ylim = ylim, log = "") : need finite 'xlim' values" When print $importance, several variables have NaN under %IncMSE. There are no NaNs in the original data. Can someone help me figure out...

...ibute `nodes', which is an n by ntree matrix of terminal node indicators. This is ignored for regression. Changes in 4.2-1: * There is now a package name space. Only generics are exported. * Some function names have been changed: partial.plot -> partialPlot var.imp.plot -> varImpPlot var.used -> varUsed * There is a new option `replace' in randomForest() (default to TRUE) indicating whether the sampling of cases is with or without replacement. * In randomForest(), the `sampsize' option now works for both classification and regression, and indicate th...

...ibute `nodes', which is an n by ntree matrix of terminal node indicators. This is ignored for regression. Changes in 4.2-1: * There is now a package name space. Only generics are exported. * Some function names have been changed: partial.plot -> partialPlot var.imp.plot -> varImpPlot var.used -> varUsed * There is a new option `replace' in randomForest() (default to TRUE) indicating whether the sampling of cases is with or without replacement. * In randomForest(), the `sampsize' option now works for both classification and regression, and indicate th...

...SR) > > > > dat1.rf <-randomForest(SR ~ X13+ X52+ X53+ X64+ X85+ X99+ X111+ > X142+ X157+ X158+ X162+ X169+ X200+ + X202+ X203+ X205+ X206+ X209+ X210+ X225+ X269+ X283+ X290+ X432+ X434+ X455+ X467+ X512, data=dat1, importance=TRUE, + proximity=TRUE, varUsed=TRUE, ntree=5000, varImpPlot=TRUE) > > > print(dat1.rf) > varImpPlot(dat1.rf) > > varUsed(dat1.rf, by.tree=FALSE, count=TRUE) > > MDSplot(dat1.rf, dat1$SR, palette=rep(1, 2), + pch=as.numeric(dat1$SR)) > > > path3 <- "C:\\Users..." > path4 <- "..." > name2 &l...

...e permutations). Here are my questions. 1) variable importance error? Is there any ways to estimate the error on the "MeanDecreaseAccuracy"? In other words, I would like to know how significant are "MeanDecreaseAccuracy" differences (and display horizontal error bars in the VarImpPlot output). I have notice that even with relatively large number of trees, I have variation in the importance values from one run to the next. Could this serve as a measure of the errors/uncertainties? 2) how to deal with variable correlation? so far, I am iterating, selecting the most important...

i am new to R and using the random forest package. is there a way to specify the x-axis scale range for the variable importance plot? many thanks. -alison -- View this message in context: http://www.nabble.com/specifying-x-axis-scale-on-random-forest-variable-importance-plot-tp19780560p19780560.html Sent from the R help mailing list archive at Nabble.com.

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: