Displaying 20 results from an estimated 3000 matches similar to: "Using MDSplot from randomForest to classify samples"
2012 Mar 23
1
Memory limits for MDSplot in randomForest package
Hello,
I am struggling to produce an MDS plot using the randomForest package
with a moderately large data set. My data set has one categorical
response variables, 7 predictor variables and just under 19000
observations. That means my proximity matrix is approximately 133000
by 133000 which is quite large. To train a random forest on this large
a dataset I have to use my institutions high
2012 Nov 22
1
Partial dependence plot in randomForest package (all flat responses)
Hi,
I'm trying to make a partial plot with package randomForest in R. After I
perform my random forest object I type
partialPlot(data.rforest, pred.data=act2, x.var=centroid, "C")
where data.rforest is my randomforest object, act2 is the original dataset,
centroid is one of the predictor and C is one of the classes in my response
variable.
Whatever predictor or response class I
2012 Aug 07
0
predicting test dataset response from training dataset with randomForest
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 <-
2006 Jan 03
1
randomForest - classifier switch
Hi
I am trying to use randomForest for classification. I am using this
code:
> set.seed(71)
> rf.model <- randomForest(similarity ~ ., data=set1[1:100,],
importance=TRUE, proximity=TRUE)
Warning message:
The response has five or fewer unique values. Are you sure you want to
do regression? in: randomForest.default(m, y, ...)
> rf.model
Call:
randomForest(x = similarity ~ .,
2010 May 04
1
randomforests - how to classify
Hi,
I'm experimenting with random forests and want to perform a binary
classification task.
I've tried some of the sample codes in the help files and things run, but I
get a message to the effect 'you don't have very many unique values in the
target - are you sure you want to do regression?' (sorry, don't know exact
message but r is busy now so can't check).
In
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
2009 Jan 10
0
Rserve/RandomForest does not work with a CSV?
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
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 ).
2008 Jul 02
1
randomForest training error
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
2023 Mar 19
1
ver el código de randomForest
Buenos días:
Otra opción es escribir directamente el nombre de la función en la
consola de R:
> randomForest
function (x, ...)
UseMethod("randomForest")
En este caso, la función randomForest() llama a UseMethod() para
seleccionar el método adecuado.
Podemos ver los métodos para randomForest con la función methods():
> methods(randomForest)
[1] randomForest.default*
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.
2007 Jun 06
0
Question on RandomForest in unsupervised mode
Hi,
I attempted to run the randomForest() function on a dataset without
predefined classes. According to the manual, running randomForest
without a response variable/class labels should result in the
function assuming you are running in unsupervised mode. In this case,
I understand that my data is all assigned to one class whereas a
second synthetic class is made up, which is assigned
2010 Apr 08
1
RandomForest how to identify two classes when only one is present
I'm trying to do:
randomForest(f, data = moths.train)
But I get this error:
Error in randomForest.default(m, y, ...) :
Need at least two classes to do classification.
When I look at the data for this, I realize there are no positive cases of
this item:
[1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0
[38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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
2011 Jan 03
1
randomForest speed improvements
Hi there,
We're trying to use randomForest to do some predictions. The test-harness
for our code is pretty straightforward:
library ('randomForest');
data202 <- read.csv ("random.csv", header=TRUE);
x<- data202[1:50000,1:6];
y<- data202[1:50000,8];
y<- y[,drop=TRUE];
x2 <- data202[50001:60000,1:6];
y2 <- data202[50001:60000,8];
y2 <-
2011 Jan 20
1
randomForest: too many elements specified?
I getting "Error in matrix(0, n, n) : too many elements specified"
while building randomForest model, which looks like memory allocation
error.
Software versions are: randomForest 4.5-25, R version 2.7.1
Dataset is big (~90K rows, ~200 columns), but this is on a big machine (
~120G RAM)
and I call randomForest like this: randomForest(x,y)
i.e. in supervised mode and not requesting
2006 Apr 18
2
installation of package "randomForest" failed
Hello
I'd like to try out some functions in the package randomForest. Therefore,
I did install this package. However, it is not possible to load the
library, although I have R-Version 2.1.1 (i.e. later than 2.0.0). The
commands I used and the Answers/Error from R is as follows:
>
install.packages("C://Programme//R//rw2011//library//randomForest_4.5-16.zip",
2009 Jan 20
1
Can't find -lg2c when installing randomForest
I have search the help archives and can't find a direct reference to the
following issue:
When installing randomForest on under CentOS 5.2 , R version 2.7.1 with gcc
4.1.2.
We receive the following error (see below, can't find –lg2c) it is in the
path!
root@abcsci12 ~]# R CMD INSTALL
/scisys/home/yanicrk/randomForest_4.5-28.tar.gz
* Installing to library
2007 Apr 29
1
randomForest gives different results for formula call v. x, y methods. Why?
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