similar to: Question on class 1, 2 output for RandomForest

Hi All, My question is in regards to an error generated when using randomForest in R. Is there a special way to format the data in order to avoid this error, or am I completely confused on what the error implies? "Error in randomForest.default(m, y, ...) : Can not handle categorical predictors with more than 32 categories." This is generated from the command line: >

It always helps to check whether you got the data into R correctly. Hint: What does str(credit) tell you? Andy > From: Melanie Vida > > Hi All, > > My question is in regards to an error generated when using > randomForest > in R. Is there a special way to format the data in order to > avoid this > error, or am I completely confused on what the error implies?

Hi All, In the script below, the importance measure for column 4 (ie MeanDecreaseGini) indicated "Inf" for V7. Running the getTree command showed that "V7" had been selected at least twice in one of the trees for Random Forest. So the "Inf" command was not generated as a result of dividing the sum of the decreases by 0. Any suggestions on what may be causing the

Just curious if anyone else has got this error before, and if so, would know what I could do (if anything) to get past it: > mtry <- tuneRF(training, trainingdata$class, ntreeTry = 500, stepFactor = 2, improve = 0.05, trace = TRUE, plot = TRUE, doBest = FALSE) mtry = 13 OOB error = 0.62% Searching left ... mtry = 7 OOB error = 1.38% -1.222222 0.05 Searching right ... mtry = 26

try with an unc path and not a drive letter. if you get the admin auth you loose the drive letter. greetz, louis > Op 7 jan. 2016 om 20:37 heeft Mike <1100100 at gmail.com> het volgende geschreven: > > Version 4.1.19-SerNet-RedHat-11.el7 on CentOS 7.1503 > > Trying to install a software app on a domain user's windows client (Win 7 > Pro). > The user and

Hi, I would like to use a random Forest model to get an idea about which variables from a dataset may have some prognostic significance in a smallish study. The default for the number of trees seems to be 500. I tried changing the default to ntree=2000 or ntree=200 and the results appear identical. Have changed mtry from mtry=5 to mtry=6 successfully. Have seen same problem on both a Windows

that was a stupid answer, sorry, i did read it correctly. post your smb.conf (sanitized) so we can have a look what we are talking about. > Op 7 jan. 2016 om 20:56 heeft L.P.H. van Belle <belle at bazuin.nl> het volgende geschreven: > > try with an unc path and not a drive letter. > if you get the admin auth you loose the drive letter. > > greetz, > louis >

Currently away from my desk. Will post smb.conf as soon as I get to ssh terminal. Thanks for your help. On Jan 7, 2016 3:05 PM, "L.P.H. van Belle" <belle at bazuin.nl> wrote: > that was a stupid answer, sorry, i did read it correctly. > > post your smb.conf (sanitized) so we can have a look what we are talking > about. > > > > Op 7 jan. 2016 om 20:56 heeft

Hi all, My old and stable backup script don't work anymore. It's based on smbclient's tar command using crX parameters for creating archive, excluding files based on basic regular expressions. The box is running Fedora core 2, fully updated: kernel-2.6.8-1.521 samba-common-3.0.7-2.FC2 samba-client-3.0.7-2.FC2 The error is easily reproducible: smbclient //ntpdc/share -A credfile \ -c

Hello everyone I need some advice if the following might be easier implemented. There are n matrixes each matrix needs to calculate one value for the rest n-1 matrixes (but not for itself). I implemented this one by two nested loops for (i in c(1:length(CRX))) { for (j in c(1:length(CRX))) if (i!=j) # where i and j are the two indexes. If i==j then is the same matrix.

Dear Researches, I am using RF (in regression way) for analize several metrics extract from image. I am tuning RF setting a loop using different range of mtry, tree and nodesize using the lower value of MSE-OOB mtry from 1 to 5 nodesize from1 to 10 tree from 1 to 500 using this paper as refery Palmer, D. S., O'Boyle, N. M., Glen, R. C., & Mitchell, J. B. O. (2007). Random Forest Models

On Tue, Aug 23, 2005 at 03:10:45PM +1000, openssh-unix-dev-request at mindrot.org wrote: > Date: Fri, 19 Aug 2005 17:56:19 +1000 > From: Darren Tucker <dtucker at zip.com.au> > Subject: Re: OpenSSH sget/sput suggestion > To: CRX Driver <crxssi at hotmail.com> > Cc: openssh-unix-dev at mindrot.org > Message-ID: <430590A3.1090506 at zip.com.au> > Content-Type:

Hello everyone. I am using ggplot and I need some help to merge these two plots into one. plot_CR<-function(x,y,agentid,CRagent){   library(ggplot2)     agent<-CRagent[[agentid]] # To make following expression shorter   ggplot((data.frame(x=CRX,y=CRY,sr=agent$sr)))+   geom_point(aes(x,y,colour=cut(sr,c(0,-10,-20,-30,-40,-50,-60,-70,-80))))+   geom_text(aes(x,y,color=cut(sr,

Dear all, seasons greetings, I had made a list of elements that I want to have  # list generator Agent<-list(id=NA, position=list(x=NA,y=NA)) # Make list of Agents AgentList<-rep(list(CRAgent),5) # Initialization. Is it shorter to do that with a lapply statement? for (i in c(1:length(CRAgentList))){   AgentList[[i]]$id=i } The created struct looks like > str(AgentList) List of 5  $

Just out of curiosity, I took the default "iris" example in the RF helpfile... but seeing the admonition against using the formula interface for large data sets, I wanted to play around a bit to see how the various options affected the output. Found something interesting I couldn't find documentation for... Just like the example... > set.seed(12) # to be sure I have

Dear all, I have a data frame that is created like that data.frame(x=CRX[-1],y=CRY[-1],z=CRagent[[1]]$sr) the output looks like 45 116 162 -30.89105988567164 46 128  79 -42.66296679571184 47 180 195 -30.45626175641315 48 114  83 -45.26843476475688 49 118  73 -46.85389245327003 How can I select only the rows that their third column is higher that -45? This will return the following 116 162

> From: luk > > I got the following results when I run radomForest with below > commands: > > qair <- read.table("train10.dat", header = T) > oz.rf <- randomForest(LESION ~ ., data = qair, ntree = 220, > importance = TRUE) > print(oz.rf) > > Call: > randomForest.formula(x = LESION ~ ., data = qair, ntree = > 220, importance =

I've built two RF objects (RF1 and RF2) and have tried to combine them, but I get the following error: Error in rf$votes + ifelse(is.na(rflist[[i]]$votes), 0, rflist[[i]]$votes) : non-conformable arrays In addition: Warning message: In rf$oob.times + rflist[[i]]$oob.times : longer object length is not a multiple of shorter object length Both RF models use the same variables, although

I have a question on the output generated by randomForest in classification mode, specifically, the confusion matrix. The confusion matrix lists the various classes and how the forest classified each one, plus the classification error. Are these numbers essentially averages over all the trees in the forest? If so, is there a way I can get the standard deviation values out of the randomForest,

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =