Displaying 20 results from an estimated 1000 matches similar to: "randomForest question [Broadcast]"
2005 Mar 23
0
Question on class 1, 2 output for RandomForest
The `1' and `2' columns are the error rates within those classes. E.g., the
last row of the `1' column should correspond to the class.error for "-", and
the last row of the `2' column to the class.error for "+". (I would
have thought that that should be fairly obvious, but I guess not. It mimics
what Breiman and Cutler's Fortran code does.) I suspect
2009 Aug 13
2
randomForest question--problem with ntree
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
2011 Nov 16
0
problem to tunning RandomForest, an unexpected result
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
2008 Jun 15
1
randomForest, 'No forest component...' error while calling Predict()
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 ).
2004 Oct 13
0
Problems with randomForest for regression
Dear list,
I am trying to do a benchmark study for my case study. It is a regression
problem. Among other models I use randomForest.
Using the following code the result is around 0.628, and this make sense
comparing with other methods. The Theil function implements Theil's U
statistic. I do not present the definition of some variables because it is not
important to understand my problem.
2013 Feb 03
3
RandomForest, Party and Memory Management
Dear All,
For a data mining project, I am relying heavily on the RandomForest and
Party packages.
Due to the large size of the data set, I have often memory problems (in
particular with the Party package; RandomForest seems to use less memory).
I really have two questions at this point
1) Please see how I am using the Party and RandomForest packages. Any
comment is welcome and useful.
2012 Jun 15
0
argument "x" is missing, with no default - Please help find argument x
R programming question, not machine learning, although that's the content.
Apologies to all for whom the following code is eye-burning. I am using
foreach() to run a simulation on a randomForest model (actually conditional
randomForest ... "party" package). The simulation is in two dimensions.
examining how "mtry" and "ntrees" are related in terms of predictive
2004 Jul 08
0
randomForest 4.3-0 released
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
2004 Jul 08
0
randomForest 4.3-0 released
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
2008 Dec 26
2
about randomForest
hello,
I want to use randomForest to classify a matrix which is 331030?42,the last column is class signal.I use ?
Memebers.rf<-randomForest(class~.,data=Memebers,proximity=TRUE,mtry=6,ntree=200) which told me" the error is matrix(0,n,n) set too elements"
then I use:
Memebers.rf<-randomForest(class~.,data=Memebers,importance=TRUE,proximity=TRUE) which told me"the error is
2006 Jan 27
1
save trained randomForest model
I used the following command to train a randomForest model
train.rf <- randomForest(grp ~ ., data=tr, ntree=100, mtry=50)
My question is how to save the trained model so that it can be loaded later for testing new samples?
Thanks,
Luk
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2010 Jul 14
1
randomForest outlier return NA
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))){
2005 Jul 21
4
RandomForest question
Hello,
I'm trying to find out the optimal number of splits (mtry parameter) for a randomForest classification. The classification is binary and there are 32 explanatory variables (mostly factors with each up to 4 levels but also some numeric variables) and 575 cases.
I've seen that although there are only 32 explanatory variables the best classification performance is reached when
2012 Aug 01
0
Questions regarding MCRestimate package
Hello,
I'm currently using MCRestimate package and I have a question regarding
the MCRestimate function.
Here is my code:
NestedCV.rf<-MCRestimate(eset, "Class", classificatin.fun="RF.wrap",
variableSel.fun="varSel.highest.var", poss.parameters=
list(var.numbers=c(100), mtry=c(10,50),
cross.outer=10,cross.inner=10,cross.repeat=3)
I'm pretty sure that I
2006 Dec 21
1
Memory problem on a linux cluster using a large data set [Broadcast]
Thank you all for your help!
So with all your suggestions we will try to run it on a computer with a 64 bits proccesor. But i've been told that the new R versions all work on a 32bits processor. I read in other posts that only the old R versions were capable of larger data sets and were running under 64 bit proccesors. I also read that they are adapting the new R version for 64 bits
2007 Sep 15
0
Question about VarSelRF
Dear list members,
I am analyzing Affymentrix gene expression data and would like to
apply the R package, VarSelRF to identifying small sets of genes that could
be used for diagnostic purpose.
Basically, the data matrix is composed of 22277 rows (genes) and 65 columns
(samples).
I did unsupervised clustering using pvclust to get 4 classes. What I would
like to do is
to get unique genes for each
2011 Dec 22
0
randomforest and AUC using 10 fold CV - Plotting results
Here is a snippet to show what i'm trying to do.
library(randomForest)
library(ROCR)
library(caret)
data(iris)
iris <- iris[(iris$Species != "setosa"),]
fit <- randomForest(factor(Species) ~ ., data=iris, ntree=50)
train.predict <- predict(fit,iris,type="prob")[,2]
2018 Jan 31
0
using randomForest() with matrix() as input results to an Error: protect(): protection stack overflow
Hello,
I'm trying to figure out a solution online but couldn't so far. I realized
that others dealt with such an error but their suggestions didn't work for
me.
So, I'm trying to run the randomForest() using this command:
rf = randomForest(classes~., data=as.matrix(train), mtry=5, ntree=2000,
importance=TRUE)
and it always results in *Error: protect(): protection stack
2008 Sep 25
0
varimp in party (or randomForest)
Hi,
There is an excellent article at http://www.biomedcentral.com/1471-2105/9/307 by Stroble, et al. describing variable importance in random forests. Does anyone have any suggestions (besides imputation or removal of cases) for how to deal with data that *have* missing data for predictor variables?
Below is an excerpt of some code referenced in the article. I have commented out one line and
2004 Oct 13
1
random forest -optimising mtry
Dear R-helpers,
I'm working on mass spectra in randomForest/R, and following the
recommendations for the case of noisy variables, I don't want to use the
default mtry (sqrt of nvariables), but I'm not sure up to which
proportion mtry/nvariables it makes sense to increase mtry without
"overtuning" RF.
Let me tell my example: I have 106 spectra belonging to 4 classes, the